ForeCast

Avi Parrack was a researcher at Forethought, where he worked on AI, space expansion, and governance. Tom Davidson is a senior research fellow at Forethought and the author of a series of reports on AI timelines, takeoff speeds, and AI-enabled coups.

They discuss:

Why SpaceX could give the US around 99% of global launch capacity once Starship is flying

How the space-based interceptors planned for Golden Dome would work

Whether the US could use this lead to "pull up the ladder" and lock rivals out of space

How rivals might fight back: jamming, hacking, ground-based lasers, and strikes on launch sites

Whether space dominance could break nuclear deterrence, and why Avi expects the US to build the capability but hold back from using it

Whether a lead in space could make up for China pulling ahead on Earth during an industrial explosion

First-mover advantages in the race to industrialise the solar system: scarce orbital slots, more chances to iterate, space robotics, and mass that never has to be launched from Earth

Why all of this could shape a US–China grand bargain, even if no space race ever happens

You can read a full transcript here.

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Will MacAskill (Senior Research Fellow at Forethought) and Mia Taylor (Research Fellow at Forethought) discuss how to use philanthropic money to do the most good during and after the intelligence explosion, and explain why wealthy donors should consider handing off their philanthropy. They talk about:

The challenges beyond AI takeover that we must address to get on track for the best futures

Why it could be valuable to spend philanthropic money on AI labour during the intelligence explosion, and how money might be spent post-ASI

Why philanthropists should consider handing off much of their giving to others, and concerns donors might have with this

You can read a full transcript here.

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Matthew Adelstein was a Visiting Scholar at Forethought and blogs as Bentham’s Bulldog, where he writes on ethics, animal welfare, and the long-run future.

He joined Fin Moorhouse to discuss:

Why Matthew thinks handoff of high-stakes decision-making to AI is the most likely route to a great future

Why locking in current human values would be a cosmic-scale catastrophe, why steering nowhere in particular is barely better, and why the alternative is building AIs that we trust to do reflective moral philosophy

Various ways handoff might manifest politically: elected AI representatives (“President Claude”), extending political rights to digital minds, or de facto handoff through gradual disempowerment of humanity

Whether handoff should be reversible (such that humans could take back control if we wanted) or if we should “tie ourselves to the mast”

Whether to task AIs with “do what’s objectively good” or “do what humans would want on reflection,” why Matthew leans toward the former, and why he expects the two to ultimately converge

If digital minds end up vastly outnumbering humans, and those digital minds deserve political rights, then consistently applied liberal-democratic principles may imply handoff as reducing expected disenfranchisement

Whether AIs can actually do philosophy: where models currently sit, bootstrapping schemes using AI-designed evals, training AIs with different epistemic constitutions and looking for convergence, and Fin’s scepticism that recursive self-evaluation works as well as it needs to

Whether we could even tell if an AI were superhuman at philosophy, given the difficulty of evaluating philosophy that’s beyond our own level of competence

Whether goodness can compete under evolutionary pressure, resource races into space, and intergalactic existential risks as an argument for top-down planning

Whether humans’ selfish preferences would saturate in a post-AGI world

Why smart AIs won’t necessarily converge on good values, and how selection against “weird” outputs (by humans’ lights) to moral reasoning could lock in something mediocre

You can read a full transcript here.

To see all Forethought's published research, visit forethought.org/research.

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Peter Salib is an Assistant Professor of Law at the University of Houston Law Center and co-director of the Center for Law & AI Risk. Simon Goldstein is an associate professor at the University of Hong Kong, a senior editor at AI Frontiers, and a visiting senior scholar at Forethought. They have written together about AI safety, AI rights, and the governance of advanced AI.

They joined Forethought’s Fin Moorhouse to discuss their new paper, Liberalism Forever. The conversation covers:

Their “null hypothesis”: today’s liberal institutions — free markets and democratic governance — may already hold most of the answers for governing the far future, and longtermists have underrated their power

Examining whether canonical social-science arguments for markets and democracy still hold under transformative AI, space colonization, and explosive growth, and claiming that most survive (and several get stronger)

Why they favour reasoning “at the margin” over designing a detailed end-state, and why proposals like viatopia and the long reflection sound liberal but risk illiberalism when actually implemented

Whether the standard case for markets — information aggregation, allocative efficiency, innovation — still bites once AGI can read off preferences directly

Why inequality is, in their view, a comparatively boring problem with a known solution (tax-and-transfer), why AI-specific taxes like a compute tax are misguided, and how the growth-versus-distribution trade-off changes when growth rates get very high

Dyson swarms and space resources: why they doubt there’s any real monopoly worry, since energy would be additive with free entry, and why property auctions might beat egalitarian allocation schemes

The arguments for democracy that persist post-AGI — public-choice/selectorate incentives and democracy as a commitment device — versus the epistemic arguments, which they think weaken

Why AGI could make autocracy more competitive (loyal AI bureaucrats and militaries removing the need for a human winning coalition), and what preserving democratic control requires in response

Handoffs to superintelligent AI and successionism, and their preferred alternative of extending the franchise to AIs with their own values rather than deferring wholesale

The history of new “technologies of democracy,” from the Federalist Papers to LLMs as impartial arbiters, and where each author thinks their own argument is weakest

You can read a full transcript here.

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Will MacAskill is a senior research fellow at Forethought and the author of What We Owe The Future. Tom Davidson is a senior research fellow at Forethought and the author of a series of reports on AI timelines, takeoff speeds, and AI-enabled coups.

In this informal conversation about early-stage research in progress, they discuss:

Why a philanthropist who takes transformative AI seriously should expect extraordinary investment returns (plausibly 10x to 100x) and how the market doesn’t seem to be pricing this in

Why AGI shouldn’t be treated as a hard deadline to spend by, and the case that most philanthropic money should be spent during the intelligence explosion rather than before it

How genuine AI substitutes for human labor would dissolve the hiring bottleneck that makes organizations so hard to scale today

How relative prices shift when cognitive labour becomes abundant, why the patent system stops making sense in that world, and the window of “crazy philanthropic bargains” open to actors who adapt faster than large institutions

The prospect of a world where only a small elite has access to superintelligent medical, financial, and strategic advice, and what it would take to avoid this

Counter-considerations to the main case, e.g., crowding out by new money, the risk that overspending attracts grifters or distorts the field, and whether a richer world will mean worse philanthropic opportunities

The risk of value drift over a long saving period, and mechanisms for binding your future self (such as irrevocably handing off control of philanthropic funds to independent, constitutionally-bound foundations)

“Differential intellectual development”: using directable AI researchers to accelerate biodefense, infosecurity, AI interpretability, and neglected armchair fields like population ethics and social choice theory

Why the case for waiting to give is much weaker for small donors

Will’s worry that the whole line of reasoning might fail if it turns out scaling philanthropy well is bottlenecked by serial real-world learning that no amount of cognitive labor can compress

You can read a full transcript here.

To see all Forethought's published research, visit forethought.org/research.

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