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UN digital tech agency launches initiative to improve trust in AI agents
The group will draft technical recommendations for identifying AI agents and keeping them under meaningful human oversight, the ITU said.
- On Thursday, the International Telecommunication Union launched a new Focus Group at the AI for Good Global Summit in Geneva to address accountability and trust concerns regarding increasingly autonomous AI agents.
- Autonomous AI agents perform independent tasks like scheduling and financial transactions, but the ITU warns these systems also risk impersonating people and making unauthorized decisions without meaningful human oversight.
- Focus Group Co-Chair Debora Comparin explained that common international foundations are necessary because "AI agents will soon negotiate, transact and make decisions on our behalf," requiring new frameworks for identity and trust.
- Technical, policy, and legal experts will convene for the group's first meeting in Paris in November and a second in Geneva in January to develop technical recommendations rather than binding regulations.
- Nations like China have already issued national standards for AI agents, and ITU Secretary General Doreen Bogdan-Martin noted this initiative aims to harmonize rules across a fragmented regulatory landscape before technology advances further.
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UN’s digital agency launches an initiative to make AI agents trustworthy
The United Nations’ digital agency has decided that AI agents are moving faster than anyone’s ability to trust them, and it wants to do something about it. On 9 July, the International Telecommunication Union used its AI for Good Summit in Geneva to launch an initiative aimed at keeping increasingly autonomous AI systems identifiable, accountable and […] This story continues at The Next Web
·Amsterdam, Netherlands (Kingdom of the)
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UN digital tech agency launches initiative to improve trust in AI agents
·New York, United States
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Total News Sources11
Leaning Left1Leaning Right2Center3Last UpdatedBias Distribution50% Center
Bias Distribution
- 50% of the sources are Center
50% Center
L 17%
C 50%
R 33%
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