MIRI’s February 2018 Newsletter

Updates

News and links

  • In “Adversarial Spheres,” Gilmer et al. investigate the tradeoff between test error and vulnerability to adversarial perturbations in many-dimensional spaces.
  • Recent posts on Less Wrong: Critch on “Taking AI Risk Seriously” and Ben Pace’s background model for assessing AI x-risk plans.
  • Solving the AI Race“: GoodAI is offering prizes for proposed responses to the problem that “key stakeholders, including [AI] developers, may ignore or underestimate safety procedures, or agreements, in favor of faster utilization”.
  • The Open Philanthropy Project is hiring research analysts in AI alignment, forecasting, and strategy, along with generalist researchers and operations staff.

This newsletter was originally posted on MIRI’s website.

MIRI’s December 2017 Newsletter and Annual Fundraiser

Our annual fundraiser is live. Discussed in the fundraiser post:

  • News  — What MIRI’s researchers have been working on lately, and more.
  • Goals — We plan to grow our research team 2x in 2018–2019. If we raise $850k this month, we think we can do that without dipping below a 1.5-year runway.
  • Actual goals — A bigger-picture outline of what we think is the likeliest sequence of events that could lead to good global outcomes.

Our funding drive will be running until December 31st.

Research updates

General updates

MIRI’s July 2017 Newsletter

The following was originally posted here.

A number of major mid-year MIRI updates: we received our largest donation to date, $1.01 million from an Ethereum investor! Our research priorities have also shifted somewhat, reflecting the addition of four new full-time researchers (Marcello Herreshoff, Sam Eisenstat, Tsvi Benson-Tilsen, and Abram Demski) and the departure of Patrick LaVictoire and Jessica Taylor.Research updates

General updates

News and links

FHI Quarterly Update (July 2017)

The following update was originally posted on the FHI website:

In the second 3 months of 2017, FHI has continued its work as before exploring crucial considerations for the long-run flourishing of humanity in our four research focus areas:

  • Macrostrategy – understanding which crucial considerations shape what is at stake for the future of humanity.
  • AI safety – researching computer science techniques for building safer artificially intelligent systems.
  • AI strategy – understanding how geopolitics, governance structures, and strategic trends will affect the development of advanced artificial intelligence.
  • Biorisk – working with institutions around the world to reduce risk from especially dangerous pathogens.

We have been adapting FHI to our growing size. We’ve secured 50% more office space, which will be shared with the proposed Institute for Effective Altruism. We are developing plans to restructure to make our research management more modular and to streamline our operations team.

We have gained two staff in the last quarter. Tanya Singh is joining us as a temporary administrator, coming from a background in tech start-ups. Laura Pomarius has joined us as a Web Officer with a background in design and project management. Two of our staff will be leaving in this quarter. Kathryn Mecrow is continuing her excellent work at the Centre for Effective Altruism where she will be their Office Manager. Sebastian Farquhar will be leaving to do a DPhil at Oxford but expects to continue close collaboration. We thank them for their contributions and wish them both the best!

Key outputs you can read

A number of co-authors including FHI researchers Katja Grace and Owain Evans surveyed hundreds of researchers to understand their expectations about AI performance trajectories. They found significant uncertainty, but the aggregate subjective probability estimate suggested a 50% chance of high-level AI within 45 years. Of course, the estimates are subjective and expert surveys like this are not necessarily accurate forecasts, though they do reflect the current state of opinion. The survey was widely covered in the press.

An earlier overview of funding in the AI safety field by Sebastian Farquhar highlighted slow growth in AI strategy work. Miles Brundage’s latest piece, released via 80,000 Hours, aims to expand the pipeline of workers for AI strategy by suggesting practical paths for people interested in the area.

Anders Sandberg, Stuart Armstrong, and their co-author Milan Cirkovic published a paper outlining a potential strategy for advanced civilizations to postpone computation until the universe is much colder, and thereby producing up to a 1030 multiplier of achievable computation. This might explain the Fermi paradox, although a future paper from FHI suggests there may be no paradox to explain.

Individual research updates

Macrostrategy and AI Strategy

Nick Bostrom has continued work on AI strategy and the foundations of macrostrategy and is investing in advising some key actors in AI policy. He gave a speech at the G30 in London and presented to CEOs of leading Chinese technology firms in addition to a number of other lectures.

Miles Brundage wrote a career guide for AI policy and strategy, published by 80,000 Hours. He ran a scenario planning workshop on uncertainty in AI futures. He began a paper on verifiable and enforceable agreements in AI safety while a review paper on deep reinforcement learning he co-authored was accepted. He spoke at Newspeak House and participated in a RAND workshop on AI and nuclear security.

Owen Cotton-Barratt organised and led a workshop to explore potential quick-to-implement responses to a hypothetical scenario where AI capabilities grow much faster than the median expected case.

Sebastian Farquhar continued work with the Finnish government on pandemic preparedness, existential risk awareness, and geoengineering. They are currently drafting a white paper in three working groups on those subjects. He is contributing to a technical report on AI and security.

Carrick Flynn began working on structuredly transparent crime detection using AI and encryption and attended EAG Boston.

Clare Lyle has joined as a research intern and has been working with Miles Brundage on AI strategy issues including a workshop report on AI and security.

Toby Ord has continued work on a book on existential risk, worked to recruit two research assistants, ran a forecasting exercise on AI timelines and continues his collaboration with DeepMind on AI safety.

Anders Sandberg is beginning preparation for a book on ‘grand futures’.  A paper by him and co-authors on the aestivation hypothesis was published in the Journal of the British Interplanetary Society. He contributed a report on the statistical distribution of great power war to a Yale workshop, spoke at a workshop on AI at the Johns Hopkins Applied Physics Lab, and at the AI For Good summit in Geneva, among many other workshop and conference contributions. Among many media appearances, he can be found in episodes 2-6 of National Geographic’s series Year Million.

AI Safety

Stuart Armstrong has made progress on a paper on oracle designs and low impact AI, a paper on value learning in collaboration with Jan Leike, and several other collaborations including those with DeepMind researchers. A paper on the aestivation hypothesis co-authored with Anders Sandberg was published.

Eric Drexler has been engaged in a technical collaboration addressing the adversarial example problem in machine learning and has been making progress toward a publication that reframes the AI safety landscape in terms of AI services, structured systems, and path-dependencies in AI research and development.

Owain Evans and his co-authors released their survey of AI researchers on their expectations of future trends in AI. It was covered in the New Scientist, MIT Technology Review, and leading newspapers and is under review for publication. Owain’s team completed a paper on using human intervention to help RL systems avoid catastrophe. Owain and his colleagues further promoted their online textbook on modelling agents.

Jan Leike and his co-authors released a paper on universal reinforcement learning, which makes fewer assumptions about its environment than most reinforcement learners. Jan is a research associate at FHI while working at DeepMind.

Girish Sastry, William Saunders, and Neal Jean have joined as interns and have been helping Owain Evans with research and engineering on the prevention of catastrophes during training of reinforcement learning agents.

Biosecurity

Piers Millett has been collaborating with Andrew Snyder-Beattie on a paper on the cost-effectiveness of interventions in biorisk, and the links between catastrophic biorisks and traditional biosecurity. Piers worked with biorisk organisations including the US National Academies of Science, the global technical synthetic biology meeting (SB7), and training for those overseeing Ebola samples among others.

Funding

FHI is currently in a healthy financial position, although we continue to accept donations. We expect to spend approximately £1.3m over the course of 2017. Including three new hires but no further growth, our current funds plus pledged income should last us until early 2020. Additional funding would likely be used to add to our research capacity in machine learning, technical AI safety and AI strategy. If you are interested in discussing ways to further support FHI, please contact Niel Bowerman.

Recruitment

Over the coming months we expect to recruit for a number of positions. At the moment, we are interested in applications for internships from talented individuals with a machine learning background to work in AI safety. We especially encourage applications from demographic groups currently under-represented at FHI.

MIRI’s June 2017 Newsletter

Research updates

General updates

News and links

Podcast: FLI 2016 – A Year In Review

For FLI, 2016 was a great year, full of our own success, but also great achievements from so many of the organizations we work with. Max, Meia, Anthony, Victoria, Richard, Lucas, David, and Ariel discuss what they were most excited to see in 2016 and what they’re looking forward to in 2017.

AGUIRRE: I’m Anthony Aguirre. I am a professor of physics at UC Santa Cruz, and I’m one of the founders of the Future of Life Institute.

STANLEY: I’m David Stanley, and I’m currently working with FLI as a Project Coordinator/Volunteer Coordinator.

PERRY: My name is Lucas Perry, and I’m a Project Coordinator with the Future of Life Institute.

TEGMARK: I’m Max Tegmark, and I have the fortune to be the President of the Future of Life Institute.

CHITA-TEGMARK: I’m Meia Chita-Tegmark, and I am a co-founder of the Future of Life Institute.

MALLAH: Hi, I’m Richard Mallah. I’m the Director of AI Projects at the Future of Life Institute.

KRAKOVNA: Hi everyone, I am Victoria Krakovna, and I am one of the co-founders of FLI. I’ve recently taken up a position at Google DeepMind working on AI safety.

CONN: And I’m Ariel Conn, the Director of Media and Communications for FLI. 2016 has certainly had its ups and downs, and so at FLI, we count ourselves especially lucky to have had such a successful year. We’ve continued to progress with the field of AI safety research, we’ve made incredible headway with our nuclear weapons efforts, and we’ve worked closely with many amazing groups and individuals. On that last note, much of what we’ve been most excited about throughout 2016 is the great work these other groups in our fields have also accomplished.

Over the last couple of weeks, I’ve sat down with our founders and core team to rehash their highlights from 2016 and also to learn what they’re all most looking forward to as we move into 2017.

To start things off, Max gave a summary of the work that FLI does and why 2016 was such a success.

TEGMARK: What I was most excited by in 2016 was the overall sense that people are taking seriously this idea – that we really need to win this race between the growing power of our technology and the wisdom with which we manage it. Every single way in which 2016 is better than the Stone Age is because of technology, and I’m optimistic that we can create a fantastic future with tech as long as we win this race. But in the past, the way we’ve kept one step ahead is always by learning from mistakes. We invented fire, messed up a bunch of times, and then invented the fire extinguisher. We at the Future of Life Institute feel that that strategy of learning from mistakes is a terrible idea for more powerful tech, like nuclear weapons, artificial intelligence, and things that can really alter the climate of our globe.

Now, in 2016 we saw multiple examples of people trying to plan ahead and to avoid problems with technology instead of just stumbling into them. In April, we had world leaders getting together and signing the Paris Climate Accords. In November, the United Nations General Assembly voted to start negotiations about nuclear weapons next year. The question is whether they should actually ultimately be phased out; whether the nations that don’t have nukes should work towards stigmatizing building more of them – with the idea that 14,000 is way more than anyone needs for deterrence. And – just the other day – the United Nations also decided to start negotiations on the possibility of banning lethal autonomous weapons, which is another arms race that could be very, very destabilizing. And if we keep this positive momentum, I think there’s really good hope that all of these technologies will end up having mainly beneficial uses.

Today, we think of our biologist friends as mainly responsible for the fact that we live longer and healthier lives, and not as those guys who make the bioweapons. We think of chemists as providing us with better materials and new ways of making medicines, not as the people who built chemical weapons and are all responsible for global warming. We think of AI scientists as – I hope, when we look back on them in the future – as people who helped make the world better, rather than the ones who just brought on the AI arms race. And it’s very encouraging to me that as much as people in general – but also the scientists in all these fields – are really stepping up and saying, “Hey, we’re not just going to invent this technology, and then let it be misused. We’re going to take responsibility for making sure that the technology is used beneficially.”

CONN: And beneficial AI is what FLI is primarily known for. So what did the other members have to say about AI safety in 2016? We’ll hear from Anthony first.

AGUIRRE: I would say that what has been great to see over the last year or so is the AI safety and beneficiality research field really growing into an actual research field. When we ran our first conference a couple of years ago, they were these tiny communities who had been thinking about the impact of artificial intelligence in the future and in the long-term future. They weren’t really talking to each other; they weren’t really doing much actual research – there wasn’t funding for it. So, to see in the last few years that transform into something where it takes a massive effort to keep track of all the stuff that’s being done in this space now. All the papers that are coming out, the research groups – you sort of used to be able to just find them all, easily identified. Now, there’s this huge worldwide effort and long lists, and it’s difficult to keep track of. And that’s an awesome problem to have.

As someone who’s not in the field, but sort of watching the dynamics of the research community, that’s what’s been so great to see. A research community that wasn’t there before really has started, and I think in the past year we’re seeing the actual results of that research start to come in. You know, it’s still early days. But it’s starting to come in, and we’re starting to see papers that have been basically created using these research talents and the funding that’s come through the Future of Life Institute. It’s been super gratifying. And seeing that it’s a fairly large amount of money – but fairly small compared to the total amount of research funding in artificial intelligence or other fields – but because it was so funding-starved and talent-starved before, it’s just made an enormous impact. And that’s been nice to see.

CONN: Not surprisingly, Richard was equally excited to see AI safety becoming a field of ever-increasing interest for many AI groups.

MALLAH: I’m most excited by the continued mainstreaming of AI safety research. There are more and more publications coming out by places like DeepMind and Google Brain that have really lent additional credibility to the space, as well as a continued uptake of more and more professors, and postdocs, and grad students from a wide variety of universities entering this space. And, of course, OpenAI has come out with a number of useful papers and resources.

I’m also excited that governments have really realized that this is an important issue. So, while the White House reports have come out recently focusing more on near-term AI safety research, they did note that longer-term concerns like superintelligence are not necessarily unreasonable for later this century. And that they do support – right now – funding safety work that can scale toward the future, which is really exciting. We really need more funding coming into the community for that type of research. Likewise, other governments – like the U.K. and Japan, Germany – have all made very positive statements about AI safety in one form or another. And other governments around the world.

CONN: In addition to seeing so many other groups get involved in AI safety, Victoria was also pleased to see FLI taking part in so many large AI conferences.

KRAKOVNA: I think I’ve been pretty excited to see us involved in these AI safety workshops at major conferences. So on the one hand, our conference in Puerto Rico that we organized ourselves was very influential and helped to kick-start making AI safety more mainstream in the AI community. On the other hand, it felt really good in 2016 to complement that with having events that are actually part of major conferences that were co-organized by a lot of mainstream AI researchers. I think that really was an integral part of the mainstreaming of the field. For example, I was really excited about the Reliable Machine Learning workshop at ICML that we helped to make happen. I think that was something that was quite positively received at the conference, and there was a lot of good AI safety material there.

CONN: And of course, Victoria was also pretty excited about some of the papers that were published this year connected to AI safety, many of which received at least partial funding from FLI.

KRAKOVNA: There were several excellent papers in AI safety this year, addressing core problems in safety for machine learning systems. For example, there was a paper from Stuart Russell’s lab published at NIPS, on cooperative IRL. This is about teaching AI what humans want – how to train an RL algorithm to learn the right reward function that reflects what humans want it to do. DeepMind and FHI published a paper at UAI on safely interruptible agents, that formalizes what it means for an RL agent not to have incentives to avoid shutdown. MIRI made an impressive breakthrough with their paper on logical inductors. I’m super excited about all these great papers coming out, and that our grant program contributed to these results.

CONN: For Meia, the excitement about AI safety went beyond just the technical aspects of artificial intelligence.

CHITA-TEGMARK: I am very excited about the dialogue that FLI has catalyzed – and also engaged in – throughout 2016, and especially regarding the impact of technology on society. My training is in psychology; I’m a psychologist. So I’m very interested in the human aspect of technology development. I’m very excited about questions like, how are new technologies changing us? How ready are we to embrace new technologies? Or how our psychological biases may be clouding our judgement about what we’re creating and the technologies that we’re putting out there. Are these technologies beneficial for our psychological well-being, or are they not?

So it has been extremely interesting for me to see that these questions are being asked more and more, especially by artificial intelligence developers and also researchers. I think it’s so exciting to be creating technologies that really force us to grapple with some of the most fundamental aspects, I would say, of our own psychological makeup. For example, our ethical values, our sense of purpose, our well-being, maybe our biases and shortsightedness and shortcomings as biological human beings. So I’m definitely very excited about how the conversation regarding technology – and especially artificial intelligence – has evolved over the last year. I like the way it has expanded to capture this human element, which I find so important. But I’m also so happy to feel that FLI has been an important contributor to this conversation.

CONN: Meanwhile, as Max described earlier, FLI has also gotten much more involved in decreasing the risk of nuclear weapons, and Lucas helped spearhead one of our greatest accomplishments of the year.

PERRY: One of the things that I was most excited about was our success with our divestment campaign. After a few months, we had great success in our own local Boston area with helping the City of Cambridge to divest its $1 billion portfolio from nuclear weapon producing companies. And we see this as a really big and important victory within our campaign to help institutions, persons, and universities to divest from nuclear weapons producing companies.

CONN: And in order to truly be effective we need to reach an international audience, which is something Dave has been happy to see grow this year.

STANLEY: I’m mainly excited about – at least, in my work – the increasing involvement and response we’ve had from the international community in terms of reaching out about these issues. I think it’s pretty important that we engage the international community more, and not just academics. Because these issues – things like nuclear weapons and the increasing capabilities of artificial intelligence – really will affect everybody. And they seem to be really underrepresented in mainstream media coverage as well.

So far, we’ve had pretty good responses just in terms of volunteers from many different countries around the world being interested in getting involved to help raise awareness in their respective communities, either through helping develop apps for us, or translation, or promoting just through social media these ideas in their little communities.

CONN: Many FLI members also participated in both local and global events and projects, like the following we’re about  to hear from Victoria, Richard, Lucas and Meia.

KRAKOVNA: The EAGX Oxford Conference was a fairly large conference. It was very well organized, and we had a panel there with Demis Hassabis, Nate Soares from MIRI, Murray Shanahan from Imperial, Toby Ord from FHI, and myself. I feel like overall, that conference did a good job of, for example, connecting the local EA community with the people at DeepMind, who are really thinking about AI safety concerns like Demis and also Sean Legassick, who also gave a talk about the ethics and impacts side of things. So I feel like that conference overall did a good job of connecting people who are thinking about these sorts of issues, which I think is always a great thing.  

MALLAH: I was involved in this endeavor with IEEE regarding autonomy and ethics in autonomous systems, sort of representing FLI’s positions on things like autonomous weapons and long-term AI safety. One thing that came out this year – just a few days ago, actually, due to this work from IEEE – is that the UN actually took the report pretty seriously, and it may have influenced their decision to take up the issue of autonomous weapons formally next year. That’s kind of heartening.

PERRY: A few different things that I really enjoyed doing were giving a few different talks at Duke and Boston College, and a local effective altruism conference. I’m also really excited about all the progress we’re making on our nuclear divestment application. So this is an application that will allow anyone to search their mutual fund and see whether or not their mutual funds have direct or indirect holdings in nuclear weapons-producing companies.

CHITA-TEGMARK:  So, a wonderful moment for me was at the conference organized by Yann LeCun in New York at NYU, when Daniel Kahneman, one of my thinker-heroes, asked a very important question that really left the whole audience in silence. He asked, “Does this make you happy? Would AI make you happy? Would the development of a human-level artificial intelligence make you happy?” I think that was one of the defining moments, and I was very happy to participate in this conference.

Later on, David Chalmers, another one of my thinker-heroes – this time, not the psychologist but the philosopher – organized another conference, again at NYU, trying to bring philosophers into this very important conversation about the development of artificial intelligence. And again, I felt there too, that FLI was able to contribute and bring in this perspective of the social sciences on this issue.

CONN: Now, with 2016 coming to an end, it’s time to turn our sites to 2017, and FLI is excited for this new year to be even more productive and beneficial.

TEGMARK: We at the Future of Life Institute are planning to focus primarily on artificial intelligence, and on reducing the risk of accidental nuclear war in various ways. We’re kicking off by having an international conference on artificial intelligence, and then we want to continue throughout the year providing really high-quality and easily accessible information on all these key topics, to help inform on what happens with climate change, with nuclear weapons, with lethal autonomous weapons, and so on.

And looking ahead here, I think it’s important right now – especially since a lot of people are very stressed out about the political situation in the world, about terrorism, and so on – to not ignore the positive trends and the glimmers of hope we can see as well.

CONN: As optimistic as FLI members are about 2017, we’re all also especially hopeful and curious to see what will happen with continued AI safety research.

AGUIRRE: I would say I’m looking forward to seeing in the next year more of the research that comes out, and really sort of delving into it myself, and understanding how the field of artificial intelligence and artificial intelligence safety is developing. And I’m very interested in this from the forecast and prediction standpoint.

I’m interested in trying to draw some of the AI community into really understanding how artificial intelligence is unfolding – in the short term and the medium term – as a way to understand, how long do we have? Is it, you know, if it’s really infinity, then let’s not worry about that so much, and spend a little bit more on nuclear weapons and global warming and biotech, because those are definitely happening. If human-level AI were 8 years away… honestly, I think we should be freaking out right now. And most people don’t believe that, I think most people are in the middle it seems, of thirty years or fifty years or something, which feels kind of comfortable. Although it’s not that long, really, on the big scheme of things. But I think it’s quite important to know now, which is it? How fast are these things, how long do we really have to think about all of the issues that FLI has been thinking about in AI? How long do we have before most jobs in industry and manufacturing are replaceable by a robot being slotted in for a human? That may be 5 years, it may be fifteen… It’s probably not fifty years at all. And having a good forecast on those good short-term questions I think also tells us what sort of things we have to be thinking about now.

And I’m interested in seeing how this massive AI safety community that’s started develops. It’s amazing to see centers kind of popping up like mushrooms after a rain all over and thinking about artificial intelligence safety. This partnership on AI between Google and Facebook and a number of other large companies getting started. So to see how those different individual centers will develop and how they interact with each other. Is there an overall consensus on where things should go? Or is it a bunch of different organizations doing their own thing? Where will governments come in on all of this? I think it will be interesting times. So I look forward to seeing what happens, and I will reserve judgement in terms of my optimism.

KRAKOVNA: I’m really looking forward to AI safety becoming even more mainstream, and even more of the really good researchers in AI giving it serious thought. Something that happened in the past year that I was really excited about, that I think is also pointing in this direction, is the research agenda that came out of Google Brain called “Concrete Problems in AI Safety.” And I think I’m looking forward to more things like that happening, where AI safety becomes sufficiently mainstream that people who are working in AI just feel inspired to do things like that and just think from their own perspectives: what are the important problems to solve in AI safety? And work on them.

I’m a believer in the portfolio approach with regards to AI safety research, where I think we need a lot of different research teams approaching the problems from different angles and making different assumptions, and hopefully some of them will make the right assumption. I think we are really moving in the direction in terms of more people working on these problems, and coming up with different ideas. And I look forward to seeing more of that in 2017. I think FLI can also help continue to make this happen.

MALLAH: So, we’re in the process of fostering additional collaboration among people in the AI safety space. And we will have more announcements about this early next year. We’re also working on resources to help people better visualize and better understand the space of AI safety work, and the opportunities there and the work that has been done. Because it’s actually quite a lot.

I’m also pretty excited about fostering continued theoretical work and practical work in making AI more robust and beneficial. The work in value alignment, for instance, is not something we see supported in mainstream AI research. And this is something that is pretty crucial to the way that advanced AIs will need to function. It won’t be very explicit instructions to them; they’ll have to be making decision based on what they think is right. And what is right? It’s something that… or even structuring the way to think about what is right requires some more research.

STANLEY: We’ve had pretty good success at FLI in the past few years helping to legitimize the field of AI safety. And I think it’s going to be important because AI is playing a large role in industry and there’s a lot of companies working on this, and not just in the US. So I think increasing international awareness about AI safety is going to be really important.

CHITA-TEGMARK: I believe that the AI community has raised some very important questions in 2016 regarding the impact of AI on society. I feel like 2017 should be the year to make progress on these questions, and actually research them and have some answers to them. For this, I think we need more social scientists – among people from other disciplines – to join this effort of really systematically investigating what would be the optimal impact of AI on people. I hope that in 2017 we will have more research initiatives, that we will attempt to systematically study other burning questions regarding the impact of AI on society. Some examples are: how can we ensure the psychological well-being for people while AI creates lots of displacement on the job market as many people predict. How do we optimize engagement with technology, and withdrawal from it also? Will some people be left behind, like the elderly or the economically disadvantaged? How will this affect them, and how will this affect society at large?

What about withdrawal from technology? What about satisfying our need for privacy? Will we be able to do that, or is the price of having more and more customized technologies and more and more personalization of the technologies we engage with… will that mean that we will have no privacy anymore, or that our expectations of privacy will be very seriously violated? I think these are some very important questions that I would love to get some answers to. And my wish, and also my resolution, for 2017 is to see more progress on these questions, and to hopefully also be part of this work and answering them.

PERRY: In 2017 I’m very interested in pursuing the landscape of different policy and principle recommendations from different groups regarding artificial intelligence. I’m also looking forward to expanding out nuclear divestment campaign by trying to introduce divestment to new universities, institutions, communities, and cities.

CONN: In fact, some experts believe nuclear weapons pose a greater threat now than at any time during our history.

TEGMARK: I personally feel that the greatest threat to the world in 2017 is one that the newspapers almost never write about. It’s not terrorist attacks, for example. It’s the small but horrible risk that the U.S. and Russia for some stupid reason get into an accidental nuclear war against each other. We have 14,000 nuclear weapons, and this war has almost happened many, many times. So, actually what’s quite remarkable and really gives a glimmer of hope is that – however people may feel about Putin and Trump – the fact is they are both signaling strongly that they are eager to get along better. And if that actually pans out and they manage to make some serious progress in nuclear arms reduction, that would make 2017 the best year for nuclear weapons we’ve had in a long, long time, reversing this trend of ever greater risks with ever more lethal weapons.

CONN: Some FLI members are also looking beyond nuclear weapons and artificial intelligence, as I learned when I asked Dave about other goals he hopes to accomplish with FLI this year.

STANLEY: Definitely having the volunteer team – particularly the international volunteers – continue to grow, and then scale things up. Right now, we have a fairly committed core of people who are helping out, and we think that they can start recruiting more people to help out in their little communities, and really making this stuff accessible. Not just to academics, but to everybody. And that’s also reflected in the types of people we have working for us as volunteers. They’re not just academics. We have programmers, linguists, people having just high school degrees all the way up to Ph.D.’s, so I think it’s pretty good that this varied group of people can get involved and contribute, and also reach out to other people they can relate to.

CONN: In addition to getting more people involved, Meia also pointed out that one of the best ways we can help ensure a positive future is to continue to offer people more informative content.

CHITA-TEGMARK: Another thing that I’m very excited about regarding our work here at the Future of Life Institute is this mission of empowering people to information. I think information is very powerful and can change the way people approach things: they can change their beliefs, their attitudes, and their behaviors as well. And by creating ways in which information can be readily distributed to the people, and with which they can engage very easily, I hope that we can create changes. For example, we’ve had a series of different apps regarding nuclear weapons that I think have contributed a lot to peoples knowledge and has brought this issue to the forefront of their thinking.

CONN: Yet as important as it is to highlight the existential risks we must address to keep humanity safe, perhaps it’s equally important to draw attention to the incredible hope we have for the future if we can solve these problems. Which is something both Richard and Lucas brought up for 2017.

MALLAH: I’m excited about trying to foster more positive visions of the future, so focusing on existential hope aspects of the future. Which are kind of the flip side of existential risks. So we’re looking at various ways of getting people to be creative about understanding some of the possibilities, and how to differentiate the paths between the risks and the benefits.

PERRY: Yeah, I’m also interested in creating and generating a lot more content that has to do with existential hope. Given the current global political climate, it’s all the more important to focus on how we can make the world better.

CONN: And on that note, I want to mention one of the most amazing things I discovered this past year. It had nothing to do with technology, and everything to do with people. Since starting at FLI, I’ve met countless individuals who are dedicating their lives to trying to make the world a better place. We may have a lot of problems to solve, but with so many groups focusing solely on solving them, I’m far more hopeful for the future. There are truly too many individuals that I’ve met this year to name them all, so instead, I’d like to provide a rather long list of groups and organizations I’ve had the pleasure to work with this year. A link to each group can be found at futureoflife.org/2016, and I encourage you to visit them all to learn more about the wonderful work they’re doing. In no particular order, they are:

Machine Intelligence Research Institute

Future of Humanity Institute

Global Catastrophic Risk Institute

Center for the Study of Existential Risk

Ploughshares Fund

Bulletin of Atomic Scientists

Open Philanthropy Project

Union of Concerned Scientists

The William Perry Project

ReThink Media

Don’t Bank on the Bomb

Federation of American Scientists

Massachusetts Peace Action

IEEE (Institute for Electrical and Electronics Engineers)

Center for Human-Compatible Artificial Intelligence

Center for Effective Altruism

Center for Applied Rationality

Foresight Institute

Leverhulme Center for the Future of Intelligence

Global Priorities Project

Association for the Advancement of Artificial Intelligence

International Joint Conference on Artificial Intelligence

Partnership on AI

The White House Office of Science and Technology Policy

The Future Society at Harvard Kennedy School

 

I couldn’t be more excited to see what 2017 holds in store for us, and all of us at FLI look forward to doing all we can to help create a safe and beneficial future for everyone. But to end on an even more optimistic note, I turn back to Max.

TEGMARK: Finally, I’d like – because I spend a lot of my time thinking about our universe – to remind everybody that we shouldn’t just be focused on the next election cycle. We have not decades, but billions of years of potentially awesome future for life, on Earth and far beyond. And it’s so important to not let ourselves get so distracted by our everyday little frustrations that we lose sight of these incredible opportunities that we all stand to gain from if we can get along, and focus, and collaborate, and use technology for good.

MIRI December 2016 Newsletter

We’re in the final weeks of our push to cover our funding shortfall, and we’re now halfway to our $160,000 goal. For potential donors who are interested in an outside perspective, Future of Humanity Institute (FHI) researcher Owen Cotton-Barratt has written up why he’s donating to MIRI this year. (Donation page.)Research updates

General updates

  • We teamed up with a number of AI safety researchers to help compile a list of recommended AI safety readings for the Center for Human-Compatible AI. See this page if you would like to get involved with CHCAI’s research.
  • Investment analyst Ben Hoskin reviews MIRI and other organizations involved in AI safety.

News and links

  • The Off-Switch Game“: Dylan Hadfield-Manell, Anca Dragan, Pieter Abbeel, and Stuart Russell show that an AI agent’s corrigibility is closely tied to the uncertainty it has about its utility function.
  • Russell and Allan Dafoe critique an inaccurate summary by Oren Etzioni of a new survey of AI experts on superintelligence.
  • Sam Harris interviews Russell on the basics of AI risk (video). See also Russell’s new Q&A on the future of AI.
  • Future of Life Institute co-founder Viktoriya Krakovna and FHI researcher Jan Leike join Google DeepMind’s safety team.
  • GoodAI sponsors a challenge to “accelerate the search for general artificial intelligence”.
  • OpenAI releases Universe, “a software platform for measuring and training an AI’s general intelligence across the world’s supply of games”. Meanwhile, DeepMind has open-sourced their own platform for general AI research, DeepMind Lab.
  • Staff at GiveWell and the Centre for Effective Altruism, along with others in the effective altruism community, explain where they’re donating this year.
  • FHI is seeking AI safety interns, researchers, and admins: jobs page.

This newsletter was originally posted here.

Artificial Intelligence and the King Midas Problem

Value alignment. It’s a phrase that often pops up in discussions about the safety and ethics of artificial intelligence. How can scientists create AI with goals and values that align with those of the people it interacts with?

Very simple robots with very constrained tasks do not need goals or values at all. Although the Roomba’s designers know you want a clean floor, Roomba doesn’t: it simply executes a procedure that the Roomba’s designers predict will work—most of the time. If your kitten leaves a messy pile on the carpet, Roomba will dutifully smear it all over the living room. If we keep programming smarter and smarter robots, then by the late 2020s, you may be able to ask your wonderful domestic robot to cook a tasty, high-protein dinner. But if you forgot to buy any meat, you may come home to a hot meal but find the aforementioned cat has mysteriously vanished. The robot, designed for chores, doesn’t understand that the sentimental value of the cat exceeds its nutritional value.

AI and King Midas

Stuart Russell, a renowned AI researcher, compares the challenge of defining a robot’s objective to the King Midas myth. “The robot,” says Russell, “has some objective and pursues it brilliantly to the destruction of mankind. And it’s because it’s the wrong objective. It’s the old King Midas problem.”

This is one of the big problems in AI safety that Russell is trying to solve. “We’ve got to get the right objective,” he explains, “and since we don’t seem to know how to program it, the right answer seems to be that the robot should learn – from interacting with and watching humans – what it is humans care about.”

Russell works from the assumption that the robot will solve whatever formal problem we define. Rather than assuming that the robot should optimize a given objective, Russell defines the problem as a two-player game (“game” as used by economists, meaning a decision problem with multiple agents) called cooperative inverse reinforcement learning (CIRL).

A CIRL game includes a person and a robot: the robot’s only purpose is to make the person happy, but it doesn’t know what the person wants. Fortunately, it can learn more about what the person wants by observing her behavior. For example, if a robot observed the human’s morning routine, it should discover how important coffee is—not to itself, of course (we don’t want robots drinking coffee), but to the human. Then, it will make coffee for the person without being asked.

What about the example of King Midas, who thought he wanted as much gold as possible? How does the approach deal with someone stating their wishes incorrectly?

“We don’t have to know what we want. That’s the whole point. It’s hard to know what we want, and what we ask for is evidence for what we really want, but it’s not ground truth,” says Russell.

The robot should learn what people want by watching their actions. Then, if someone asks for something that’s technically incorrect, the robot will understand their underlying wish. Russell adds, “The robot—if it had been there—would have told Midas that he didn’t really want everything turned to gold, maybe just a few choice objects that he might point at from time to time and say the magic word.”

AI Off-Switch

Russell and his Berkeley colleagues also recently announced further progress toward ensuring safe AI, with a paper on ensuring an AI’s off-switch is always accessible. An off-switch is often suggested to guarantee a robot doesn’t harm humans – if the robot goes bad, just turn it off! But what if the AI anticipates that and disables its off switch?

Russell and his team propose solving this by providing a level of uncertainty in the robot’s objective. They created another CIRL game in which the robot chooses to announce its intentions, which gives the human a chance to switch it off, or to plunge ahead with its plan, bypassing human oversight.

They showed that a robot with a fixed objective will take the second choice and disable its off-switch. But if there is uncertainty about the objective, the robot will reason that a human decision to switch the robot off would imply the announced intention is undesirable. Because its goal is to make the human happy, the robot accepts being switched off. The robot has a positive incentive not to disable the off-switch, and that incentive is directly tied to the robot’s uncertainty about the human’s true objective.

Ensuring AI Safety

In addition to his research, Russell is also one of the most vocal and active AI safety researchers concerned with ensuring a stronger public understanding of the potential issues surrounding AI development.

He recently co-authored a rebuttal to an article in the MIT Technology Review, which claimed that real AI scientists weren’t worried about the existential threat of AI. Russell and his co-author summed up why it’s better to be cautious and careful than just assume all will turn out for the best:

“Our experience with Chernobyl suggests it may be unwise to claim that a powerful technology entails no risks. It may also be unwise to claim that a powerful technology will never come to fruition. On September 11, 1933, Lord Rutherford, perhaps the world’s most eminent nuclear physicist, described the prospect of extracting energy from atoms as nothing but “moonshine.” Less than 24 hours later, Leo Szilard invented the neutron-induced nuclear chain reaction; detailed designs for nuclear reactors and nuclear weapons followed a few years later. Surely it is better to anticipate human ingenuity than to underestimate it, better to acknowledge the risks than to deny them. … [T]he risk [of AI] arises from the unpredictability and potential irreversibility of deploying an optimization process more intelligent than the humans who specified its objectives.”

This summer, Russell received a grant of over $5.5 million from the Open Philanthropy Project for a new research center, the Center for Human-Compatible Artificial Intelligence, in Berkeley. Among the primary objectives of the Center will be to study this problem of value alignment, to continue his efforts toward provably beneficial AI, and to ensure we don’t make the same mistakes as King Midas.

“Look,” he says, “if you were King Midas, would you want your robot to say, ‘Everything turns to gold? OK, boss, you got it.’ No! You’d want it to say, ‘Are you sure? Including your food, drink, and relatives? I’m pretty sure you wouldn’t like that. How about this: you point to something and say ‘Abracadabra Aurificio’ or something, and then I’ll turn it to gold, OK?’”

This article is part of a Future of Life series on the AI safety research grants, which were funded by generous donations from Elon Musk and the Open Philanthropy Project.

2300 Scientists from All Fifty States Pen Open Letter to Incoming Trump Administration

The following press release comes from the Union of Concerned Scientists.

Unfettered Science Essential to Decision Making; the Science Community Will Be Watching

WASHINGTON (November 30, 2016)—More than 2300 scientists from all fifty states, including 22 Nobel Prize recipients, released an open letter urging the Trump administration and Congress to set a high bar for integrity, transparency and independence in using science to inform federal policies. Some notable signers have advised Republican and Democratic presidents, from Richard Nixon to Barack Obama.

“Americans recognize that science is critical to improving our quality of life, and when science is ignored or politically corrupted, it’s the American people who suffer,” said physicist Lewis Branscomb, professor at the University of California, San Diego School of Global Policy and Strategy, who served as vice president and chief scientist at IBM and as director of the National Bureau of Standards under President Nixon. “Respect for science in policymaking should be a prerequisite for any cabinet position.”

The letter lays out several expectations from the science community for the Trump administration, including that he appoint a cabinet with a track record of supporting independent science and diversity; independence for federal science advisors; and sufficient funding for scientific data collection. It also outlines basic standards to ensure that federal policy is fully informed by the best available science.

For example, federal scientists should be able to: conduct their work without political or private-sector interference; freely communicate their findings to Congress, the public and their scientific peers; and expose and challenge misrepresentation, censorship or other abuses of science without fear of retaliation.

“A thriving federal scientific enterprise has enormous benefits to the public,” said Nobel Laureate Carol Greider, director of molecular biology and genetics at Johns Hopkins University. “Experts at federal agencies prevent the spread of diseases, ensure the safety of our food and water, protect consumers from harmful medical devices, and so much more. The new administration must ensure that federal agencies can continue to use science to serve the public interest.”

The letter also calls on the Trump administration and Congress to resist attempts to weaken the scientific foundation of laws such as the Clean Air Act and Endangered Species Act. Congress is expected to reintroduce several harmful legislative proposals—such as the REINS Act and the Secret Science Reform Act—that would increase political control over the ability of federal agency experts to use science to protect public health and the environment.

The signers encouraged their fellow scientists to engage with the executive and legislative branches, but also to monitor the activities of the White House and Congress closely. “Scientists will pay close attention to how the Trump administration governs, and are prepared to fight any attempts to undermine of the role of science in protecting public health and the environment,” said James McCarthy, professor of biological oceanography at Harvard University and former president of the American Association for the Advancement of Science. “We will hold them to a high standard from day one.”

MIRI’S November 2016 Newsletter

Post-fundraiser update: Donors rallied late last month to get us most of the way to our first fundraiser goal, but we ultimately fell short. This means that we’ll need to make up the remaining $160k gap over the next month if we’re going to move forward on our 2017 plans. We’re in a good position to expand our research staff and trial a number of potential hires, but only if we feel confident about our funding prospects over the next few years.Since we don’t have an official end-of-the-year fundraiser planned this time around, we’ll be relying more on word-of-mouth to reach new donors. To help us with our expansion plans, donate at https://intelligence.org/donate/ — and spread the word!

Research updates

General updates

News and links

MIRI October 2016 Newsletter

The following newsletter was originally posted on MIRI’s website.

Our big announcement this month is our paper “Logical Induction,” introducing an algorithm that learns to assign reasonable probabilities to mathematical, empirical, and self-referential claims in a way that outpaces deduction. MIRI’s 2016 fundraiser is also live, and runs through the end of October.

Research updates

General updates

  • We wrote up a more detailed fundraiser post for the Effective Altruism Forum, outlining our research methodology and the basic case for MIRI.
  • We’ll be running an “Ask MIRI Anything” on the EA Forum this Wednesday, Oct. 12.
  • The Open Philanthropy Project has awarded MIRI a one-year $500,000 grant to expand our research program. See also Holden Karnofsky’s account of how his views on EA and AI have changed.

News and links

MIRI September 2016 Newsletter

Research updates

General updates

News and links

See the original newsletter on MIRI’s website.

New Center for Human-Compatible AI

Congratulations to Stuart Russell for his recently announced launch of the Center for Human-Compatible AI!

The new center will be funded, primarily, by a generous grant from the Open Philanthropy Project for $5,555,550. The center will focus on research around value alignment, in which AI systems and robots will be trained using novel methods to understand what a human really wants, rather than just relying on initial programming.

Russell is most well known as the co-author of Artificial Intelligence: A Modern Approach, which has become the standard textbook for AI students. However, in recent years, Russell has also become an increasingly strong advocate for AI safety research and ensuring that the goals of artificial intelligence align with the goals of humans.

In a statement to FLI, Russell (who also sits on the FLI Science Advisory Board) said:

“I’m thrilled to have the opportunity to launch a serious attack on what is — as Nick Bostrom has called it — ‘the essential task of our age.’ It’s obviously in the very early stages but our work (funded previously by FLI) is already leading to some surprising new ideas for what safe AI systems might look like. We hope to find some excellent PhD students and postdocs and to start training the researchers who will take this forward.”

An example of this type of research can be seen in a paper published this month by Russell and other researchers on Cooperative Inverse Reinforcement Learning (CIRL). In inverse reinforcement learning, the AI system or robot has to learn a human’s goals by observing the human in a real-world or simulated environment, and CIRL is a potentially more effective method for teaching the AI to achieve this. In a press release about the new center, the Open Philanthropy Project listed other possible research avenues, such as:

  • “Value alignment through, e.g., inverse reinforcement learning from multiple sources (such as text and video).
  • “Value functions defined by partially observable and partially defined terms (e.g. ‘health,’ ‘death’).
  • “The structure of human value systems, and the implications of computational limitations and human inconsistency.
  • “Conceptual questions including the properties of ideal value systems, tradeoffs among humans and long-term stability of values.”

Other funders include the Future of Life Institute and the Defense Advanced Research Projects Agency, and other co-PIs and collaborators include:

  • Pieter Abbeel, Associate Professor of Computer Science, UC Berkeley
  • Anca Dragan, Assistant Professor of Computer Science, UC Berkeley
  • Tom Griffiths, Professor of Psychology and Cognitive Science, UC Berkeley
  • Bart Selman, Professor of Computer Science, Cornell University
  • Joseph Halpern, Professor of Computer Science, Cornell University
  • Michael Wellman, Professor of Computer Science, University of Michigan
  • Satinder Singh Baveja, Professor of Computer Science, University of Michigan

In their press release, the Open Philanthropy Project added:

“We also believe that supporting Professor Russell’s work in general is likely to be beneficial. He appears to us to be more focused on reducing potential risks of advanced artificial intelligence (particularly the specific risks we are most focused on) than any comparably senior, mainstream academic of whom we are aware. We also see him as an effective communicator with a good reputation throughout the field.”

MIRI August 2016 Newsletter

Research updates

General updates

  • Our 2015 in review, with a focus on the technical problems we made progress on.
  • Another recap: how our summer colloquium series and fellows program went.
  • We’ve uploaded our first CSRBAI talks: Stuart Russell on “AI: The Story So Far” (video), Alan Fern on “Toward Recognizing and Explaining Uncertainty” (video), and Francesca Rossi on “Moral Preferences” (video).
  • We submitted our recommendations to the White House Office of Science and Technology Policy, cross-posted to our blog.
  • We attended IJCAI and the White House’s AI and economics event. Furman on technological unemployment (video) and other talks are available online.
  • Talks from June’s safety and control in AI event are also online. Speakers included Microsoft’s Eric Horvitz (video), FLI’s Richard Mallah (video), Google Brain’s Dario Amodei (video), and IARPA’s Jason Matheny (video).

News and links

See the original newsletter on MIRI’s website.

Effective Altruism 2016

The Effective Altruism Movement

Edit: The following article has been updated to include more highlights as well as links to videos of the talks.

How can we more effectively make the world a better place? Over 1,000 concerned altruists converged at the Effective Altruism Global conference this month in Berkeley, CA to address this very question. For two and a half days, participants milled around the Berkeley campus, attending talks, discussions, and workshops to learn more about efforts currently underway to improve our ability to not just do good in the world, but to do the most good.

Those who arrived on the afternoon of Friday, August 5 had the opportunity to mingle with other altruists and attend various workshops geared toward finding the best careers, improving communication, and developing greater self-understanding and self-awareness.

But the conference really kicked off on Saturday, August 6, with talks by Will MacAskill and Toby Ord, who both helped found the modern effective altruistism movement. Ord gave the audience a brief overview of the centuries of science and philosophy that provided the base for effective altruism. “Effective altruism is to the pursuit of good as the scientific revolution is to the pursuit of truth,” he explained. Yet, as he pointed out, effective altruism has only been a real “thing” for five years.

Will MacAskill

Will MacAskill introduced the conference and spoke of the success the EA movement has had in the last year.

Toby Ord speaking about the history of effective altruism.

Toby Ord spoke about the history of effective altruism.

 

MacAskill took the stage after Ord to highlight the movement’s successes over the past year, including coverage by such papers as the New York Times and the Washington Post. And more importantly, he talked about the significant increase in membership they saw this year, as well as in donations to worthwhile causes. But he also reminded the audience that a big part of the movement is the process of effective altruism. He said:

“We don’t know what the best way to do good is. We need to figure that out.”

For the rest of the two days, participants considered past charitable actions that had been most effective, problems and challenges altruists face today, and how the movement can continue to grow. There were too many events to attend them all, but there were many highlights.

Highlights From the Conference

When FLI cofounder, Jaan Tallin, was asked why he chose to focus on issues such as artificial intelligence, which may or may not be a problem in the future, rather than mosquito nets, which could save lives today, he compared philanthropy to investing. Higher risk investments have the potential for a greater payoff later. Similarly, while AI may not seem like much of  threat to many people now, ensuring it remains safe could save billions of lives in the future. Tallin spoke as part of a discussion on Philanthropy and Technology.

Jaan Tallin speaking remotely about his work with EA efforts.

Jaan Tallin speaking remotely about his work with EA efforts.

Martin Reese, a member of FLI’s Science Advisory Board, argued that we are in denial of the seriousness of our risks. At the same time, he said that minimizing risks associated with technological advances can only be done “with great difficulty.”  He encouraged EA participants to figure out which threats can be dismissed as science fiction and which are legitimate, and he encouraged scientists to become more socially engaged.

As if taking up that call to action, Kevin Esvelt talked about his own attempts to ensure gene drive research in the wild is accepted and welcomed by local communities. Gene drives could be used to eradicate such diseases as malaria, schistosomiasis, Zika, and many others, but fears of genetic modification could slow research efforts. He discussed his focus on keeping his work as open and accessible as possible, engaging with the public to allow anyone who might be affected by his research to have as much input as they want. “Closed door science,” he added, “is more dangerous because we have no way of knowing what other people are doing.”  A single misstep with this early research in his field could imperil all future efforts for gene drives.

Kevin Esvelt talks about his work with CRISPR and gene drives.

Kevin Esvelt talks about his work with CRISPR and gene drives.

That same afternoon, Cari Tuna, President of the Open Philanthropy Project, sat down with Will McAskill for an interview titled, “Doing Philosophy Better,” which focused on her work with OPP and Effective Altruism and how she envisions her future as a philanthropist. She highlighted some of the grants she’s most excited about, which include grants to Give Directly, Center for Global Development, and Alliance for Safety and Justice. When asked about how she thought EA could improve, she emphasized, “We consider ourselves a part of the Effective Altruism community, and we’re excited to help it grow.” But she also said, “I think there is a tendency toward overconfidence in the EA community that sometimes undermines our credibility.” She mentioned that one of the reasons she trusted GiveWell was because of their self reflection. “They’re always asking, ‘how could we be wrong?'” she explained, and then added, “I would really love to see self reflection become more of a core value of the effective altruism community.”

cari tuna

Cari Tuna interviewed by Will McAskill (photo from the Center for Effective Altruism).

The next day, FLI President, Max Tegmark, highlighted the top nine myths of AI safety, and he discussed how important it is to dispel these myths so researchers can focus on the areas necessary to keep AI beneficial. Some of the most distracting myths include arguments over when artificial general intelligence could be created, whether or not it could be “evil,” and goal-oriented issues. Tegmark also added that the best thing people can do is volunteer for EA groups.

During the discussion about the risks and benefits of advanced artificial intelligence, Dileep George, cofounder of Vicarious, reminded the audience why this work is so important. “The goal of the future is full unemployment so we can all play,” he said. Dario Amodei of OpenAI emphasized that having curiosity and trying to understand how technology is evolving can go a long way toward safety. And though he often mentioned the risks of advanced AI, Toby Ord, a philosopher and research fellow with the Future of Humanity Institute, also added, “I think it’s more likely than not that AI will contribute to a fabulous outcome.” Later in the day, Chris Olah, an AI researcher at Google Brain and one of the lead authors of the paper, Concrete Problems in AI Safety, explained his work as trying to build a bridge to futuristic problems by doing empirical research today.

Moderator Riva-Melissa Tez, Dario Amodei, George Dileep, and Toby Ord at the Risks and Benefits of Advanced AI discussion.

Moderator Riva-Melissa Tez, Dario Amodei, Dileep George, and Toby Ord at the Risks and Benefits of Advanced AI discussion. (Not pictured, Daniel Dewey)

FLI’s Richard Mallah gave a talk on mapping the landscape of AI safety research threads. He showed how there are many meaningful dimensions along which such research can be organized, how harmonizing the various research agendas into a common space allows us to reason about different kinds of synergies and dependencies, and how consideration of the white space in such representations can help us find both unknown knowns and unknown unknowns about the space.

Tara MacAulay, COO at the Centre for Effective Altruism, spoke during the discussion on “The Past, Present, and Future of EA.” She talked about finding the common values in the movement and coordinating across skill sets rather than splintering into cause areas or picking apart who is and who is not in the movement. She said, “The opposite of effective altruism isn’t ineffective altruism. The opposite of effective altruism is apathy, looking at the world and not caring, not doing anything about it . . . It’s helplessness. . . . throwing up our hands and saying this is all too hard.”

MacAulay also moderated a panel discussion called, Aggregating Knowledge, which was significant, not only for its thoughtful content about accessing, understanding, and communicating all of the knowledge available today, but also because it was an all-woman panel. The panel included Sarah Constantin, Amanda Askell, Julia Galef, and Heidi McAnnaly, who discussed various questions and problems the EA community faces when trying to assess which actions will be most effective. MacAulay summarized the discussion at the end when she said, “Figuring out what to do is really difficult but we do have a lot of tools available.” She concluded with a challenge to the audience to spend five minutes researching some belief they’ve always had about the world to learn what the evidence actually says about it.

aggregating knowledge

Sarah Constantin, Amanda Askell, Julia Galef, Heidi McAnnaly, and Tara MacAulay (photo from the Center for Effective Altruism).

Prominent government leaders also took to the stage to discuss how work with federal agencies can help shape and impact the future. Tom Kalil, Deputy Director for Technology and Innovation highlighted how much of today’s technology, from cell phones to Internet, got its start in government labs. Then, Jason Matheny, Director of IARPA, talked about how delays in technology can actually cost millions of lives. He explained that technology can make it less costly to enhance moral developments and that, “ensuring that we have a future counts a lot.”

Tom Kalil speaks about the history of government research and its impact on technology.

Tom Kalil speaks about the history of government research and its impact on technology.

Jason Matheny talks about how employment with government agencies can help advance beneficial technologies.

Jason Matheny talks about how employment with government agencies can help advance beneficial technologies.

Robin Hanson, author of The Age of Em, talked about his book and what the future will hold if we continue down our current economic path while the ability to create brain emulation is developed. He said that if creating ems becomes cheaper than paying humans to do work, “that would change everything.” Ems would completely take over the job market and humans would be pushed aside. He explained that some people might benefit from this new economy, but it would vary, just as it does today, with many more people suffering from poverty and fewer gaining wealth.

Robin Hanson talks to a group about how brain emulations might take over the economy and what their world will look like.

Robin Hanson talks to a group about how brain emulations might take over the economy and what their world will look like.

 

Applying EA to Real Life

Lucas Perry, also with FLI, was especially impressed by the career workshops offered by 80,000 Hours during the conference. He said:

“The 80,000 Hours workshops were just amazing for giving new context and perspective to work. 80,000 Hours gave me the tools and information necessary to reevaluate my current trajectory and see if it really is best of all possible paths for me and the world.

In the end, I walked away from the conference realizing I had been missing out on something so important for most of my life. I found myself wishing that effective altruism, and organizations like 80,000 Hours, had been a part of my fundamental education. I think it would have helped immensely with providing direction and meaning to my life. I’m sure it will do the same for others.”

In total, 150 people spoke over the course of those two and a half days. MacAskill finally concluded the conference with another call to focus on the process of effective altruism, saying:

“Constant self-reflection, constant learning, that’s how we’re going to be able to do the most good.”

 

View from the conference.

View from the conference.

The Evolution of AI: Can Morality be Programmed?

Click here to see this page in other languages: Chinese  

The following article was originally posted on Futurism.com.

Recent advances in artificial intelligence have made it clear that our computers need to have a moral code. Disagree? Consider this: A car is driving down the road when a child on a bicycle suddenly swerves in front of it. Does the car swerve into an oncoming lane, hitting another car that is already there? Does the car swerve off the road and hit a tree? Does it continue forward and hit the child?

Each solution comes with a problem: It could result in death.

It’s an unfortunate scenario, but humans face such scenarios every day, and if an autonomous car is the one in control, it needs to be able to make this choice. And that means that we need to figure out how to program morality into our computers.

Vincent Conitzer, a Professor of Computer Science at Duke University, recently received a grant from the Future of Life Institute in order to try and figure out just how we can make an advanced AI that is able to make moral judgments…and act on them.

MAKING MORALITY

At first glance, the goal seems simple enough—make an AI that behaves in a way that is ethically responsible; however, it’s far more complicated than it initially seems, as there are an amazing amount of factors that come into play. As Conitzer’s project outlines, “moral judgments are affected by rights (such as privacy), roles (such as in families), past actions (such as promises), motives and intentions, and other morally relevant features. These diverse factors have not yet been built into AI systems.”

That’s what we’re trying to do now.

In a recent interview with Futurism, Conitzer clarified that, while the public may be concerned about ensuring that rogue AI don’t decide to wipe-out humanity, such a thing really isn’t a viable threat at the present time (and it won’t be for a long, long time). As a result, his team isn’t concerned with preventing a global-robotic-apocalypse by making selfless AI that adore humanity. Rather, on a much more basic level, they are focused on ensuring that our artificial intelligence systems are able to make the hard, moral choices that humans make on a daily basis.

So, how do you make an AI that is able to make a difficult moral decision?

Conitzer explains that, to reach their goal, the team is following a two path process: Having people make ethical choices in order to find patterns and then figuring out how that can be translated into an artificial intelligence. He clarifies, “what we’re working on right now is actually having people make ethical decisions, or state what decision they would make in a given situation, and then we use machine learning to try to identify what the general pattern is and determine the extent that we could reproduce those kind of decisions.”

In short, the team is trying to find the patterns in our moral choices and translate this pattern into AI systems. Conitzer notes that, on a basic level, it’s all about making predictions regarding what a human would do in a given situation, “if we can become very good at predicting what kind of decisions people make in these kind of ethical circumstances, well then, we could make those decisions ourselves in the form of the computer program.”

However, one major problem with this is, of course, that morality is not objective — it’s neither timeless nor universal.

Conitzer articulates the problem by looking to previous decades, “if we did the same ethical tests a hundred years ago, the decisions that we would get from people would be much more racist, sexist, and all kinds of other things that we wouldn’t see as ‘good’ now. Similarly, right now, maybe our moral development hasn’t come to its apex, and a hundred years from now people might feel that some of the things we do right now, like how we treat animals, is completely immoral. So there’s kind of a risk of bias and with getting stuck at whatever our current level of moral development is.”

And of course, there is the aforementioned problem regarding how complex morality is. “Pure altruism, that’s very easy to address in game theory, but maybe you feel like you owe me something based on previous actions. That’s missing from the game theory literature, and so that’s something that we’re also thinking about a lot—how can you make this, what game theory calls ‘Solutions Concept’—sensible? How can you compute these things?”

To solve these problems, and to help figure out exactly how morality functions and can (hopefully) be programmed into an AI, the team is combining the methods from computer science, philosophy, and psychology “That’s, in a nutshell, what our project is about,” Conitzer asserts.

But what about those sentient AI? When will we need to start worrying about them and discussing how they should be regulated?

THE HUMAN-LIKE AI

According to Conitzer, human-like artificial intelligence won’t be around for some time yet (so yay! No Terminator-styled apocalypse…at least for the next few years).

“Recently, there have been a number of steps towards such a system, and I think there have been a lot of surprising advances….but I think having something like a ‘true AI,’ one that’s really as flexible, able to abstract, and do all these things that humans do so easily, I think we’re still quite far away from that,” Conitzer asserts.

True, we can program systems to do a lot of things that humans do well, but there are some things that are exceedingly complex and hard to translate into a pattern that computers can recognize and learn from (which is ultimately the basis of all AI).

“What came out of early AI research, the first couple decades of AI research, was the fact that certain things that we had thought of as being real benchmarks for intelligence, like being able to play chess well, were actually quite accessible to computers. It was not easy to write and create a chess-playing program, but it was doable.”

Indeed, today, we have computers that are able to beat the best players in the world in a host of games—Chess and Alpha Go, for example.

But Conitzer clarifies that, as it turns out, playing games isn’t exactly a good measure of human-like intelligence. Or at least, there is a lot more to the human mind. “Meanwhile, we learned that other problems that were very simple for people were actually quite hard for computers, or to program computers to do. For example, recognizing your grandmother in a crowd. You could do that quite easily, but it’s actually very difficult to program a computer to recognize things that well.”

Since the early days of AI research, we have made computers that are able to recognize and identify specific images. However, to sum the main point, it is remarkably difficult to program a system that is able to do all of the things that humans can do, which is why it will be some time before we have a ‘true AI.’

Yet, Conitzer asserts that now is the time to start considering what the rules we will use to govern such intelligences. “It may be quite a bit further out, but to computer scientists, that means maybe just on the order of decades, and it definitely makes sense to try to think about these things a little bit ahead.” And he notes that, even though we don’t have any human-like robots just yet, our intelligence systems are already making moral choices and could, potentially, save or end lives.

“Very often, many of these decisions that they make do impact people and we may need to make decisions that we will typically be considered to be a morally loaded decision. And a standard example is a self-driving car that has to decide to either go straight and crash into the car ahead of it or veer off and maybe hurt some pedestrian. How do you make those trade-offs? And that I think is something we can really make some progress on. This doesn’t require superintelligent AI, this can just be programs that make these kind of trade-offs in various ways.”

But of course, knowing what decision to make will first require knowing exactly how our morality operates (or at least having a fairly good idea). From there, we can begin to program it, and that’s what Conitzer and his team are hoping to do.

So welcome to the dawn of moral robots.

This interview has been edited for brevity and clarity. 

This article is part of a Future of Life series on the AI safety research grants, which were funded by generous donations from Elon Musk and the Open Philanthropy Project.

MIRI’s June 2016 Newsletter

Research updates

General updates

News and links

MIRI May 2016 Newsletter

Research updates

General updates

News and links

This newsletter was originally posted here.

Nuclear Weapons Are Scary — But We Can Do Something About Them

We’re ending our Huffington Post nuclear security series on a high note, with this article by Susi Snyder, explaining how people can take real action to decrease the threat of nuclear weapons.

Nuclear weapons are scary. The risk of use by accident, intention or terror. The climate consequences. The fact that they are designed and built to vaporize thousands of people with the push of a button. Scary. Fortunately, there is something we can do.

We know that nuclear weapons are scary, but we must be much louder in defining them as unacceptable, as illegitimate. By following the money, we can cut it off, and while this isn’t the only thing necessary to make nuclear weapons extinct, it will help.

That’s why we made Don’t Bank on the Bomb. Because we want to do something about nuclear weapons. Investments are not neutral. Financing and investing are active choices, based on a clear assessment of a company and its plans. Any financial service delivered to a company by a financial institution or other investor gives a tacit approval of their activities. To make nuclear weapons, you need money. Governments pay for a lot of things, but the companies most heavily involved in producing key components for nuclear warheads need additional investment — from banks, pension funds, and insurance companies — to sustain the working capital they need to maintain and modernize nuclear bombs.

We can steer these companies in a new direction. We can influence their decision making, by making sure our own investments don’t go anywhere near nuclear weapon producing companies. Choosing to avoid investment in controversial items or the companies that make them — from tobacco to nuclear arms — can result in changed policies and reduces the chances of humanitarian harm. Just as it wasn’t smokers that got smoking banned indoors across the planet, it’s not likely that the nuclear armed countries will show the normative leadership necessary to cut off the flow of money to their nuclear bomb producers.

Public exclusions by investors have a stigmatizing effect on companies associated with illegitimate activities. There are lots of examples from child labor to tobacco where financial pressure had a profound impact on industry. While it is unlikely that divestment by a single financial institution or government would enough for a company to cancel its nuclear weapons associated contracts, divestment by even a few institutions, or countries, for the same reason can affect a company’s strategic direction.

It’s worked before.

Divestment, and legal imperatives to divest are powerful tools to compel change. The divestment efforts in the 1980s around South Africa are often cited as having a profound impact on ending the Apartheid Regime. Global efforts divesting from tobacco stocks, have not ended the production or sale of tobacco products, but have compelled the producing companies to significantly modify behaviors — and they’ve helped to delegitimize smoking.

According to a 2013 report by Oxford University “in almost every divestment campaign … from adult services to Darfur, tobacco to Apartheid, divestment campaigns were effective in lobbying for restricting legislation affecting stigmatized firms.” The current global fossil fuel divestment campaign is mobilizing at all levels of society to stigmatize relationships with the fossil fuel industry resulting in divestment by institutions representing over $3.4 trillion in assets, and inspiring investment towards sustainable energy solutions.

US company Lockheed Martin, which describes itself as the worlds largest arms manufacturer, announced it ceased its involvement with the production of rockets, missiles or other delivery systems for cluster munitions and stated it will not accept such orders in the future. The arms manufacturer expressed the hope that its decision to cease the activities in the area of cluster munitions would enable it to be included in investors portfolios again, thereby suggesting that pressure by financial institutions had something to do with its decision.

In Geneva right now, governments are meeting to discuss new legal measures to deal with the deadliest weapons. The majority of governments want action- and want it now. Discussions are taking place about negotiating new legal instruments — new international law about nuclear weapons. The majority of the world’s governments are calling for a comprehensive new treaty to outlaw nuclear weapons.

And they’re talking about divestment too. For example, the Ambassador from Jamaica said:

“A legally-binding instrument on prohibition of nuclear weapons would also serve as a catalyst for the elimination of such weapons. Indeed, it would encourage nuclear weapon states and nuclear umbrella states to stop relying on these types of weapons of mass destruction for their perceived security. Another notable impact of a global prohibition is that it would encourage financial institutions to divest their holdings in nuclear weapons companies.”

Governments are talking about divestment, and it’s something you can do too.

If you have a bank account, find out if your bank invests in nuclear weapon producing companies. You can either look at our website and see if your bank is listed, or you can ask your bank directly. We found that a few people, asking the same bank about questionable investments, was enough to get that bank to adopt a policy preventing them from having any relationship with nuclear weapon producing companies.

Anyone, no matter where they are can have some influence over nuclear weapons decision making. From the heads of government to you from your very own pocket — everyone can do something about this issue. It doesn’t take a lot of time, or money, to make a difference, but it does take you. Together we can stop the scary threat of massive nuclear violence. If you want to help end the threat of nuclear weapons, then put your money where your mouth is, and Don’t Bank on the Bomb.

A Call for Russia and the U.S. to Cooperate in Protecting Against Nuclear Terrorism

The following post was written by Former Secretary of Defense William J. Perry and California Governor Jerry Brown as part of our Huffington Post series on nuclear security.

We believe that the likelihood of a nuclear catastrophe is greater today than it was during the Cold War. In the Cold War our nation lived with the danger of a nuclear war starting by accident or by miscalculation. Indeed, the U.S. had three false alarms during that period, any one of which might have resulted in a nuclear war, and several crises, including the Cuban Missile Crisis, which could have resulted in a nuclear war from a miscalculation on either side.

When the Cold War ended, these dangers receded, but with the increasing hostility between the U.S. and Russia today, they are returning, endangering both of our countries. In addition to those old dangers, two new dangers have arisen—nuclear terrorism, and the possibility of a regional nuclear war. Neither of those dangers existed during the Cold War, but both of them are very real today. In particular, the prospect of a nuclear terror attack looms over our major cities today.

Both Al Qaeda and ISIL have tried to acquire nuclear weapons, and no one should doubt that if they succeeded they would use them. Because the security around nuclear weapons is so high, it is unlikely (but not impossible) that they could buy or steal a nuclear bomb. But if they could obtain some tens of kilograms of highly enriched uranium (HEU), they could make their own improvised nuclear bomb. A significant quantity of HEU is held by civilian organizations, with substantially lower security than in military facilities. Recognizing this danger, President Obama initiated the Nuclear Security Summit meetings, whose objective was to eliminate fissile material not needed, and to provide enhanced security for the remainder.

That program—involving the leaders of over 50 nations that possessed fissile material, has been remarkably successful. In 1992, 52 countries had weapons-usable nuclear material; in 2010, the year of the first Summit, that number stood at 35. Just six years later, we are down to 24, as 11 more countries have eliminated their stocks of highly enriched uranium and plutonium. Additionally, security has been somewhat improved for the remaining material. But progress has stalled, much more remains to be done, and the danger of a terror group obtaining fissile material is still unacceptably high.

A quantity of HEU the size of a basketball would be sufficient to make an improvised nuclear bomb that had the explosive power of the Hiroshima bomb and was small enough to fit into a delivery van. Such a bomb, delivered by van (or fishing boat) and detonated in one of our cities, could essentially destroy that city, causing hundreds of thousands of casualties, as well as major social, political, and economic disruptions.

The danger of this threat is increasing every day; indeed, we believe that our population is living on borrowed time. If this catastrophe were allowed to happen, our society would never be the same. Our political system would respond with frenzied actions to ensure that it would not happen again, and we can assume that, in the panic and fear that would ensue, some of those actions would be profoundly unwise. How much better if we took preventive measures now—measures that increase our safety while still preserving our democracy and our way of life.

Two actions cry out to be taken. One is the international effort to improve the security of fissile material. The Nuclear Security Summits have made a very good start in that direction, but they are now over, and the pressure to reduce supplies of fissile material and improve security for the remainder predictably will falter. It is imperative to keep up this pressure, either through continuing summits, or through an institutional process that would be created by the nations that attended the summits and that would be managed by the Disarmament Agency of the UN, which would be given additional powers for that purpose. The U.S. should take the lead to ensure that a robust follow-on program is established.

Beyond that, and perhaps even more importantly, the U.S. and Russia, the nations that possess 90 percent of the world’s fissile material, should work closely together, including cooperation in intelligence about terror groups, to ensure that a terror group never obtains enough material to destroy one of their cities. After all, these two nations not only possess most of the fissile material, they are also the prime targets for a terror attack. Moscow and St. Petersburg are in as great a danger as Washington, D.C. and New York City.

Sen. Sam Nunn has proposed that Russia and the U.S. form a bilateral working group specifically charged with outlining concrete actions they could take that would greatly lessen the danger of Al Qaeda or ISIL obtaining enough fissile material to make improvised nuclear bombs. Whatever disagreements exist between our two countries—and they are real and serious—certainly we could agree to work together to protect our cities from destruction.

If our two countries were successful in cooperating in this important area, they might be encouraged to cooperate in other areas of mutual interest, and, in time, even begin to work to resolve other differences. The security of the whole world would be improved if they could do so.

Even with these efforts, we cannot be certain that a terror group could not obtain fissile material. But we can greatly lower that probability by taking responsible actions to protect our societies. If a nuclear bomb were to go off in one of our cities, we would move promptly to take actions that could prevent another attack. So why not do it now? Timely action can prevent the catastrophe from occurring, and can ensure that the preventive actions we take are thoughtful and do not make unnecessary infringements on our civil liberties.