Matthijs Maas
Senior Research Fellow (Law & Artificial Intelligence), Legal Priorities Project
Research Affiliate, Centre for the Study of Existential Risk.
https://www.matthijsmaas.com/ | https://linktr.ee/matthijsmaas
Matthijs Maas
Senior Research Fellow (Law & Artificial Intelligence), Legal Priorities Project
Research Affiliate, Centre for the Study of Existential Risk.
https://www.matthijsmaas.com/ | https://linktr.ee/matthijsmaas
Thanks for the overview! You might also be interested in this (forthcoming) report and lit review: https://docs.google.com/document/d/12AoyaISpmhCbHOc2f9ytSfl4RnDe5uUEgXwzNJhF-fA/edit?usp=drivesdk
I previously drew on Adler’s work to derive lessons for (military) AI governance, in: https://www.tandfonline.com/doi/abs/10.1080/13523260.2019.1576464
I will! Though likely in the form of a long form report that’s still in draft, planning to write it out in the next months. Can share a (very rough) working draft if you PM me.
Thanks for collating this, Zach! Just to note, my ‘TAI Governance: a Literature Review’ is publicly shareable—but since we’ll be cleaning up the main doc as a report the coming week, could you update the link to this copy? https://docs.google.com/document/d/1CDj_sdTzZGP9Tpppy7PdaPs_4acueuNxTjMnAiCJJKs/edit#heading=h.5romymfdade3
Thanks for collating these comments—that’s useful to get that overview.
FWIW, some people at CSER have done good work on this broad topic, working with researchers at Chinese institutions—e.g. https://link.springer.com/article/10.1007/s13347-020-00402-x
This is awful—Nathan was such an engaging and bright scholar, generous with his comments and insights. I had been hoping to see much more of his work in this field. Thank you for sharing this.
I’ve got a number of literature reviews and overview reports on this coming out soon, can share you on a draft if of interest. See also the primer / overview at https://forum.effectivealtruism.org/posts/isTXkKprgHh5j8WQr/strategic-perspectives-on-transformative-ai-governance
+1 to this proposal and focus.
On ‘technical levers to make AI coordination/regulation enforceable’, there is a fair amount of work suggesting that e.g. arms control agreements have often dependend on/been enabled by new technological avenues for enabling unilateral monitoring (or for enabling cooperative, but non-intrusive monitoring—e.g. sensors on missile factories, as part of the US-USSR INF Treaty), have been instrumental (see Coe and Vaynmann 2020 ).
That doesn’t mean that it’s always an unalloyed good: there are indeed cases where new capabilities can introduce new security or escalation risks (e.g. Vaynmann 2021); they can also perversely hold up negotiations; e.g. Richard Burns (link, introduction) discusses a case where the involvement of engineers in designing a monitoring system for the Comprehensive Test Ban Treaty, actually held up negotiations of the regime, basically because the engineers focused excessively on technical perfection of the monitoring system [beyond a level of assurance that would’ve been strictly politically required by the contracting parties], which enabled opponents of the treaty to paint it as not giving sufficiently good guarantees.
Still, beyond improving enforcement, there’s interesting work on ways that AI technology could speed up and support the negotiation of treaty regimes (Deeks 2020, 2020b, Maas 2021), both for AI governance specifically, and in supporting international cooperation more broadly.
That’s a great suggestion, I will aim to add that for each!
A few additional papers that look into this topic, that might be of interest: https://dl.acm.org/doi/10.1145/3278721.3278766
https://www.mdpi.com/2409-9287/6/3/53
https://www.tandfonline.com/doi/abs/10.1080/13523260.2019.1576464?journalCode=fcsp20
And (more narrowly focused on NAT in LAWS) https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3161446
Thanks for this post, I found it very interesting.
More that I’d like to write after reflection, but briefly—on further possible scenario variables, on either the technical or governance side, I’m working out a number of these here https://docs.google.com/document/d/1Mlt3rHcxJCBCGjSqrNJool0xB33GwmyH0bHjcveI7oc/edit# , and would be interested to discuss.
Thanks for these points! I like the rephrasing of it as ‘levers’ or pathways, thosea re also good.
A downside of the term ‘strategic perspective’ is certainly that it implies that you need to ‘pick one’, that a categorical choice needs to be made amongst them. However:
-it is clearly possible to combine and work across a number of these perspectives simultaneously, so they’re not mutually exclusive in terms of interventions; -in fact, under existing uncertainty over TAI timelines and governance conditions (i.e. parameters), it is probably preferable to pursue such a portfolio approach, rather than adopt any one perspective as the ‘consensus one’.
still, as tamgent notes, this mostly owes to our current uncertainty: once you start to take stronger positions on (or assign certain probabilities to) particular scenarios, not all of these pathways are an equally good investment of resources -indeed, some of these approaches will likely entail actions that will stand in tension to one another’s interventions (e.g. Anticipatory perspectives would recommend talking explicitly about AGI to policymakers; some versions of Path-setting, Network-building, or Pivotal Engineering would prefer to avoid that (for different reasons). A partisan perspective would prefer actions that might align the community with one actor; that might stand in tension to actions taken by a Coalitional (or multilateral Path-setting) perspectives; etc.).
I do agree that the ‘Perspectives’ framing may be too suggestive of an exclusive, coherent position that people in this space must take, when what I mean is more a loosely coherent cluster of views.
--
@tamgent “it seems hard to span more than two beliefs next to each other on any axis as an individual to me” could you clarify what you meant by this?
Thanks for the catch on the table, I’ve corrected it!
And yeah, there’s a lot of drawbacks to the table format—and a scatterplot would be much better (though unfortunately I’m not so good with editing tools, would appreciate recommendations for any). In the meantime, I’ll add in your disclaimer for the table.
I’m aiming to restart posting on the sequence later this month, would appreciate feedback and comments.
To some extend, I’d prefer not yet to anchor people too much, before finishing the entire sequence. I’ll aim to circle around later and have more deep reflection on my own commitments. In fact, one reason why I’m doing this project is that I notice I have rather large uncertainties over these different theories myself, and want to think through their assumptions and tradeoffs.
Still, while going into more detail on it later, I think it’s fair that I provide some disclaimers about my own preferences, for those who wish to know them before going in:
[preferences below break]
… … … …
TLDR: my currently (weakly held) perspective is something like ’(a) as default, pursue portfolio approach consisting of interventions from Exploratory, Prosaic Engineering, Path-setting, Adaptation-enabling, Network-building, and Environment-shaping perspectives: (b) under extremely short timelines and reasonably good alignment chances, switch to Anticipatory and Pivotal Engineering; (c) under extremely low alignment success probability, switch to Containing;”
This seems grounded in a set of predispositions / biases / heuristics that are something like:
Given I’ve quite a lot of uncertainty about key (technical and governance) parameters, I’m hesitant to commit to any one perspective and prefer portfolio approaches. —That means I lean towards strategic perspectives that are more information-providing (Exploratory), more robustly compatible with- and supportive of many others (Network-building, Environment-shaping), and/or more option-preserving and flexible (Adaptation-enabling); —conversely, for these reasons I may have less affinity for perspectives that potentially recommend far-reaching, hard-to-reverse actions under limited information conditions (Pivotal Engineering, Containing, Anticipatory);
My academic and research background (governance; international law) probably gives me a bias towards the more explicitly ‘regulatory’ perspectives (Anticipatory, Path-setting, Adaptation-enabling), especially in multilateral version (Coalitional); and a bias against perspectives that are more exclusively focused on the technical side alone (eg both Engineering perspectives), pursue more unilateral actions (Pivotal Engineering, Partisan), or which seek to completely break or go beyond existing systems (System-changing)
There are some perspectives (Adaptation-enabling, Containing) that have remained relatively underexplored within our community. While I personally am not yet convinced that there’s enough ground to adopt these as major pillars for direct action, from an Exploratory meta-perspective I am eager to see these options studied in more detail.
I am aware that under very short timelines, many of these perspectives fall away or begin looking less actionable;
[ED: I probably ended up being more explicit here than I intended to; I’d be happy to discuss these predispositions, but also would prefer to keep discussion of specific approaches concentrated in the perspective-specific posts (coming soon).
(apologies for very delayed reply)
Broadly, I’d see this as:
‘anticipatory’ if it is directly tied to a specific policy proposal or project we want to implement (‘we need to persuade everyone of the risk, so they understand the need to implement this specific governance solution’),
‘environment-shaping’ (aimed at shaping key actors’ norms and/or perceptions), if we do not have a strong sense of what policy we want to see adopted, but we would like to inform these actors to come up with the right choices themselves, once convinced.
Thanks for this analysis, I found this a very interesting report! As we’ve discussed, there are a number of convergent lines of analysis, which Di Cooke, Kayla Matteucci and I also came to for our research paper ‘Military Artificial Intelligence as Contributor to Global Catastrophic Risk’ on the EA Forum ( link ; SSRN).
Although by comparison we focused more on the operational and logistical limits to producing and using LAWS swarms en masse, and we sliced the nuclear risk escalation scenarios slightly different. We also put less focus on the question of ‘given this risk portfolio, what governance interventions are more/less useful’.
This is part of ongoing work (including a larger project and article that also examines the military developers/operators angle on AGI alignment/misuse risks, and the ‘arsenal overhang (extant military [& nuclear] infrastructures) as a contributor to misalignment risk’ arguments (for the latter, see also some of Michael Aird’s discussion here), though that had to be cut from this chapter for reasons of length and focus.
strong +1 to everything Markus suggests here.
Other journals (depending on the field) could include Journal of Strategic Studies, Contemporary Security Policy, Yale Journal of Law & Technology, Minds & Machines, AI & Ethics, ‘Law, Innovation and Technology’, Science and Engineering Ethics, Foresight, …
As Markus mentions, there are also sometimes good disciplinary journals that have special issue collections on technology—those can be opportunities to get it into high-profile journals even if they are usually more aversive to tech-focused pieces (e.g. I got a piece into Melbourne Journal of International Law); though it really depends what audiences you’re trying to reach / position your work into.
Thanks Nuño! I don’t think I’ve got well thought out views on relative importance or rankings of these work streams; I’m mostly focused on understanding scenarios in which my own work might be more or less impactful (I also should note that if some lines of research mentioned here seem much more impactful, that may be more a result of me being more familiar with them, and being able to give a more detailed account of what the research is trying to get at / what threat models and policy goals it is connected to).
On your second question, as with other academic institutes, I believe it’s actually both doable and common for donors or funders to support some of CSER’s themes or lines of work but not others. Some institutional funders (e.g. for large academic grants) will often focus on particular themes or risks (rather than e.g. ‘X-risk’ as a general class), and therefore want to ensure their funding is going to just that work. The same has been the case for individual donations, to support certain projects we’ve done, I think.
[ED: -- see link to CSER donation form. Admittedly, this web form doesn’t clearly allow you to specify different lines of work to support, but in practice this could be arranged in a bespoke way—by sending an email to director@cser.cam.ac.uk indicating what area of work one would want to support.]
The Legal Priorities Project’s research agenda also includes consideration of s-risks, alongside with x-risks and other type of trajectory changes, though I do agree this remains somewhat under-integrated with other parts of the long-termist AI governance landscape (in part, I speculate, because the perspective might face [even] more inferential distance from the concerns of AI policymakers than x-risk focused work).
This is very interesting, thanks for putting this together! FWIW, you might also be interested in some of the other terms I’ve been collecting for a related draft report ( see shared draft at https://docs.google.com/document/d/1RNlHOt32nBn3KLRtevqWcU-1ikdRQoz-CUYAK0tZVz4/edit , pg 18 onwards)