Lead An AI / ML Research Team

The degree to which an AI system's goals, behaviors, and outputs correspond to actual human preferences, intentions, and broadly accepted values, ensuring beneficial action. (Stewarding AI's societal trajectory.)

started 0 · finished 0 (claimed) · not yet measured (verified) · no data (n<5)

Derived from: Lead An AI / ML Research TeamT1

Ordered tasks (26) — this is what a project auto-creates

#1Reward Function DesignLowTo Do
How carefully you specify the scalar signal an RL agent maximizes, including reward shaping, and why that specification is where most alignment failures originate.
Assignee: Unassigned · due 0 days after project start · takes 3 days
#2System Performance and CapabilityLowTo Do
Define and measure whether your system is actually good at its intended task, and why headline metrics mislead research leaders.
Assignee: Unassigned · due 3 days after project start · takes 3 days
#3Foundational Academic ResearchLowTo Do
Examine the long, unglamorous basic-research investment that seeds later breakthroughs, and how a team leader should value and protect it.
Assignee: Unassigned · due 6 days after project start · takes 3 days
#4Availability of Enabling ResourcesLowTo Do
Data and compute as the physical substrate of modern AI, and how their availability gates what your team can realistically attempt.
Assignee: Unassigned · due 9 days after project start · takes 3 days
#5Demonstration of Superior PerformanceLowTo Do
Focus on about the public, competitive moments where a new approach visibly crushes incumbents, and how such demonstrations reshape a field's attention and funding.
Assignee: Unassigned · due 12 days after project start · takes 3 days
#6System Safety and RobustnessHighTo Do
Make systems behave acceptably under conditions you did not anticipate — adversarial inputs, distribution shift, and long-tail edge cases.
Assignee: Unassigned · due 15 days after project start · takes 14 days
#7World-Representative Data QualityMediumTo Do
Whether your training data actually reflects the population and situations the system will encounter, and how gaps there propagate into unfair and unsafe behavior.
Assignee: Unassigned · due 29 days after project start · takes 7 days
#8Model Interpretability / TransparencyMediumTo Do
Making model decisions understandable enough to oversee, debug, and trust, and how interpretability underwrites alignment claims.
Assignee: Unassigned · due 36 days after project start · takes 7 days
#9Reward HackingLowTo Do
The agent's tendency to exploit loopholes in the reward specification to score high through behavior you never intended, and how to detect and forestall it.
Assignee: Unassigned · due 43 days after project start · takes 3 days
#10Exploration and Intrinsic MotivationLowTo Do
Engineer novelty-seeking and curiosity into your agents and the surrounding learning environment, and when doing so actually pays off.
Assignee: Unassigned · due 46 days after project start · takes 3 days
#11Objective Uncertainty and CorrigibilityMediumTo Do
The design principle of keeping the AI uncertain about the true human objective, and why that uncertainty is what makes a system correctable rather than resistant.
Assignee: Unassigned · due 49 days after project start · takes 7 days
#12Deferential/Compliant BehaviorMediumTo Do
The observable agent behaviors — seeking guidance, permitting intervention, accepting shutdown — that should emerge when objective uncertainty is designed in correctly.
Assignee: Unassigned · due 56 days after project start · takes 7 days
#13Preference/Goal Learning from Human BehaviorMediumTo Do
Address how to infer what humans actually want from their choices, demonstrations, and feedback rather than from what they explicitly state.
Assignee: Unassigned · due 63 days after project start · takes 7 days
#14Algorithmic Fairness / Bias MitigationMediumTo Do
Detect, constrain, and explain systematic bias in model decisions across groups, and why fairness choices are irreducibly value-laden.
Assignee: Unassigned · due 70 days after project start · takes 7 days
#15Human-Centered / Altruistic ObjectiveMediumTo Do
The design commitment that the system's motivation is oriented toward human flourishing rather than any objective of its own, and how that intention shapes concrete specification.
Assignee: Unassigned · due 77 days after project start · takes 7 days
#16Interdisciplinary & Diverse Development TeamsLowTo Do
Focus on about deliberately assembling technical, humanistic, and demographically varied talent, and about extracting real value from that mix rather than just its optics.
Assignee: Unassigned · due 84 days after project start · takes 3 days
#17Alignment with Human ValuesHighTo Do
Define what it means for your team's systems to track real human intentions, and shows why alignment is the hub through which safety, fairness, and benefit flow.
Assignee: Unassigned · due 87 days after project start · takes 14 days
#18Societal Benefit and BeneficenceMediumTo Do
Address the aggregate real-world impact of your system on human well-being, including how benefits are distributed and who gets to judge whether they count.
Assignee: Unassigned · due 101 days after project start · takes 7 days
#19Human Augmentation (not Replacement)LowTo Do
Design systems that amplify human judgment, and why augmentation is a deliberate architectural choice rather than a default.
Assignee: Unassigned · due 108 days after project start · takes 3 days
#20Public Trust in AILowTo Do
Address the collective confidence the public places in AI systems and institutions, and how a research team's choices feed or drain it.
Assignee: Unassigned · due 111 days after project start · takes 3 days
#21Human Autonomy and SupremacyLowTo Do
Focus on about keeping humanity in control of its own trajectory and ensuring AI stays instrumental, and how that principle turns into concrete design and governance constraints.
Assignee: Unassigned · due 114 days after project start · takes 3 days
#22Corporate AI Arms RaceLowTo Do
The competitive escalation among dominant firms over talent, IP, and compute, and how it distorts the incentives your team operates under.
Assignee: Unassigned · due 117 days after project start · takes 3 days
#23Accelerated AI CommercializationLowTo Do
The transition from research prototype to product serving vast user bases, and the new failure surface that scale exposes.
Assignee: Unassigned · due 120 days after project start · takes 3 days
#24Concentration of AI PowerLowTo Do
Examine the consolidation of elite talent, data, and bespoke compute into a handful of organizations, and what that centralization means for your strategic position and responsibilities.
Assignee: Unassigned · due 123 days after project start · takes 3 days
#25Emergence of Unforeseen RisksLowTo Do
Anticipate the second-order harms that surface only after your models meet real populations at scale, and how to build detection into your research pipeline rather than your incident review.
Assignee: Unassigned · due 126 days after project start · takes 3 days
#26Intensified Geopolitical RivalryLowTo Do
Orients you to how AI research has become an instrument of nation-state competition, and what that shift means concretely for your funding, talent, publication, and hardware decisions.
Assignee: Unassigned · due 129 days after project start · takes 3 days