Human values remain key to responsible AI in 2026
summary
Argues that abundant streaming data from satellites and sensors shifts disaster risk work from theory to real-time rescue vs. long-term planning, shows universities launching degree programs in data science and AI to supply needed skills, and recommends building and bench-testing AI pipelines with controlled scenarios so tools are evaluated before rollout — testing before mass deployment. Urges encoding human values and virtues into agentic AI so automated decisions match societal priorities.
AI-written summary · about
chapters (6)
- 0:00Start
- 0:30How Data Changed Risk Analysis
- 1:49Universities Adapting to the AI Era
- 3:59The Ethics of AI and Data-Driven Systems
- 5:24Testing AI Before Deployment
- 5:59Why Human Judgment Still Matters
related talks
23mThe AI Dilemma — Steering towards a More Humane Future
19mMoral Outsourcing: Humanity in the age of AI
40mSocially responsible AI: Practical tools for robust design
44mPanel: Building responsible, human-centric AI models
44mAI, Corporate Responsibility & Democratic Legitimacy
01h 08mWHOSE DIGITAL FUTURE? ENGAGING CITIZENS IN AI DEVELOPMENT AND IMPACT ASSESSMENT
47mHow can we make the most of Ethics applied to AI?
35mFrom hype to responsibility: what works & matters for whom in data and AI?