AVOIDING THE PRECIPICE

2017-09-20 · Source: AI Roadmap Institute Blog - Medium · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation · Depth: Intermediate, long

Summary

The AI Roadmap Institute hosted a workshop on May 29, 2017, in Prague, to address the critical issue of avoiding a "winner-takes-all" race in artificial general intelligence (AGI) development that could compromise safety. The workshop, attended by researchers from CSER, GoodAI, and KISK MUNI, focused on defining the problem, identifying key actors, and visualizing potential AGI race scenarios through example roadmaps. This initiative is a preparatory step for the AI Race Avoidance round of the General AI Challenge, a citizen science project by GoodAI with a $5 million fund, aiming to broaden AI safety research beyond its current community. The goal is to foster interdisciplinary discussion and promote transparent, cooperative approaches to AGI development, mitigating risks associated with rapid, competitive deployment.

Key takeaway

For AI Scientists and Research Scientists focused on AGI development, prioritizing collaborative safety measures over competitive speed is paramount. You should actively participate in cross-disciplinary discussions and open research initiatives to build trust and share knowledge, thereby mitigating the risks of a rushed, unsafe AGI deployment. Consider contributing to platforms like the General AI Challenge to collectively address race avoidance and ensure beneficial AGI outcomes.

Key insights

Avoiding an AGI development race is crucial to prevent safety compromises and requires broad, cooperative engagement.

Principles

• First-mover advantage in AGI will be decisive.
• Cooperation reduces race dynamics and enhances safety.
• Transparency is essential for solving complex AI safety problems.

Method

Roadmapping, using linear or decision-driven scenarios, helps visualize potential AGI development paths, identify actors, and suggest mitigation strategies for negative futures, considering different timescales and viewpoints.

In practice

• Engage diverse disciplines in AI safety discussions.
• Foster low-stake cooperation among AI developers.
• Promote open and transparent AI safety research.

Topics

• Artificial General Intelligence
• AI Safety
• AI Race Avoidance
• Cooperative AI Development
• Scenario Planning

Best for: AI Scientist, Research Scientist, AI Researcher, AI Ethicist, Policy Maker

Related on AIssential

• Roadmapping the AI race to help ensure safe development of AGI — Roadmapping AGI development helps anticipate risks and opportunities, especially concerning safety and societal impact.
• Report from the AI Race Avoidance Workshop — Mitigating an AI race requires understanding its dynamics, incentivizing cooperation, and fostering global, transparent dialogue.
• The Arrival of AGI with Shane Legg (co-founder of DeepMind) — AGI is rapidly approaching, necessitating urgent societal and ethical preparedness for its transformative impact.
• The inaugural Redwood Research podcast — AI safety requires pragmatic strategies, acknowledging both technical challenges and organizational realities, to manage escalating risks.
• Anthropic urges industry coordination to allow for a 'pause' in AI development if risks grow — Rapid AI advancement, especially recursive self-improvement, necessitates a coordinated global pause mechanism to mitigate control and security risks.
• Are there lessons from high-reliability engineering for AGI safety? — High-reliability engineering principles are incompatible with AGI's emergent, unspecified nature, yet some rigorous safety approach is essential.

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by AI Roadmap Institute Blog - Medium.