Who Bears the Costs When AI Fails?
If an AI system causes harm due to its actions, who should carry the burden – companies, governments or someone else?
Encoding Social Good: Can We Teach AI to Be Fair?
Explore techniques like constrained optimization helping develop AI that encodes social goods like fairness.
Explainable AI – Understanding the Reasoning Behind Decisions
AI explainability techniques like LIME and Shapley values are bringing transparency to automated decisions – explore how they work.
Keeping AI Accountable and Fair
As AI systems make ever more consequential decisions, how can we ensure they remain ethical, fair and accountable?
Establishing Trust Between Humans and AI
As AI becomes more capable, building mutual trust is crucial. We look at ideas like transparency and value alignment.
Establishing Guardrails for AI Systems
What guardrails and controls can we put in place to ensure AI systems remain beneficial, ethical, and aligned with human values?
Can AI Help Us Save the Planet?
Learn how artificial intelligence and machine learning are being used to create innovative solutions for environmental challenges like climate change and pollution.
AI Safety: Avoiding Unintended Consequences
How can we proactively address safety and oversight for increasingly autonomous AI systems?
Humans in the Loop: Keys for Responsible AI
By keeping humans actively involved in AI systems, we can retain meaningful oversight and control over these powerful technologies.
Human Oversight: Key to Ethical AI
As AI grows more powerful, human oversight helps ensure these systems remain ethical and aligned with human values.