TLDR: Even if transformative AI systems are technically aligned and deployed with good intentions, there will likely be an “uncanny valley” between the time such systems are created and their value is equitably distributed. In the interim, there is a risk of mass suffering being inflicted on those least proximate to the creation of these systems. This creates an argument for a research and policy agenda on “AI adaptation”, which pushes resources and policy ideas toward ensuring that the disruptive effects of transformative AI systems are minimized while we cross to the other side of the uncanny valley.
I am thankful for the following papers which helped inspire me to write this post. These include the thoughts of Markus Anderlung on AI misuse, the work of David Kreuger and Andrew Critch on AI research considerations, the chapter by Ben Garfinkel on AI in historical perspective, and various papers by Allan Defoe including those on cooperative AI, AI governance opportunities, and technological determinism. I am also grateful to, amongst many papers from CSER and GCRI, this paper on transformative AI and this paper on resilience to global catastrophe. Thank you also to others who discussed this idea with me and helped me refine this post, your advice was invaluable.
Members of the Effective Altruism, X-risk, AI Safety, security, policy (and overlapping) communities have dedicated a laudable amount of effort and resources towards ensuring that our collective future can best take advantage of the benefits of advanced artificial intelligence while minimizing the potential existential risks from advanced AI systems. These efforts can be (broadly) divided into two buckets:
Efforts in this space are, as most people reading this post would agree, critical and should be supported in whatever way each of us can.
At the same time, I feel that this intense focus on alignment and deployment might come at the expense of attention towards potentially less important and yet nonetheless vital issues. I call this set of issues, “AI Adaptation”. Borrowing from the vast literature on climate adaptation, I define AI adaptation as the project of adjusting to the expected disruptive effects of advanced artificial intelligence in order to moderate or avoid harm from these disruptions.
The argument here is as follows. Even if one can assume that:
and
There is still considerable work to be done to fashion global economic, political, and social systems that are prepared for a transition to this fundamentally different world.
There is a growing amount of research adjacent to this adaptation space such as that mentioned at the top of this post (the paper by Jess Whittlestone and Ross Gruetzemacher is particularly relevant). There is also an increasing amount of research that seeks to ensure that we also pay considerable attention to the risks from artificial intelligence systems on the road to transformative artificial intelligence, such as that focusing on disinformation, developments in biotechnology, and lethal autonomous weapons.
I believe an important aspect of research that is still under-considered is the disruptive economic and political impact of transformative artificial intelligence, in particular on those who live outside the United States and Western Europe. I believe that in the absence of a project dedicated to funding and research adaptation to the disruptive effects of transformative artificial intelligence, there may be mass suffering in many parts of the world.
In arguing for this project, I am making the following assumptions:
As someone who has grown up and spent most of his life in a non-Western country without significant international influence, I am acutely concerned about this uncanny valley. In particular, I am worried that mass economic disruption is likely to inflict suffering on likely hundreds of millions of people who are least responsible for the technology’s creation, least proximate to its benefits, and most vulnerable to its disruptive effects. Here is a possible illustration of my argument:
This illustration is, hopefully, concerning.
As the tone of this post makes clear, the intention of this illustration is not to provide an argument against the development of advanced AI systems, and it is definitely not an argument against investing resources towards technical alignment and responsible deployment of AI systems.
Instead, the intention here is to argue for resources and attention (being, for now, agnostic as to how much) to be devoted towards AI Adaptation to ensure that ‘best-case’ advanced AI scenarios account for the potentially transformative negative effects of advanced AI systems on those least likely to be protected against economic and political disruptions. The use of the term ‘adaptation’ here is intentional – I am assuming an inevitability to the development of transformative artificial intelligence, in the same way that many assume that significant disruptions from climate change are now more or less inevitable and have incentivized efforts to adapt to a warmer climate.
In writing this post, I have attempted to be fairly generous in making my assumptions, but perhaps it is important to note some things that could go much worse which would make this case for adaptation much stronger:
These factors, and many others, are likely to have a significant bearing on the case for and nature of adaptation and each deserve further independent inquiry of their own in this context.
While this project of adaptation requires much deeper thought and reflection – as well as institutional resources devoted to its inquiry – I think the following tentative policies could be of interest to those who find value in researching this problem:
As those focused on global governance, economics, politics, and many others are aware, each of these proposals has significant problems and likely much greater issues with tractability. The intention is to pitch them tentatively as a starting point for crafting a policy and research agenda which can aid adaptation efforts.
I believe such a project would be of interest to those vested in reducing the risks from emerging technologies, as well as those dedicating their lives to reducing global poverty and improving global health and well-being. It may also provide an additional general argument against the rapid development of advanced AI systems without careful thought of the consequences.
Great stuff! Agree on the importance of this. I think that the odds of this type of disruption being harmful are largely a function of the pace at which increasingly capable systems are deployed. If you go from e.g. 20% task automation capabilities to 100% over the course of 50 years that will be a far less disruptive, and more equitable transition than one that happens over 3 years. In the fast takeoff case, I would argue that there probably is not a social safety net program that could adequately counter the social, political and economic disruptions caused by that pace of deployment. So while we should plan to build societal resilience via institution building and shoring up safety nets for sure, we may want to consider “figure out optimal deployment speeds for aligned, not dangerous, misuse-proof AI” and “figure out the right regulatory mechanisms to enforce those timelines on AI labs” to this research agenda as well.