Ikigai’s Post

Do we really need #AI to monitor #AI? Or, projecting it to the human world, do we need a four-eyes principle in the AI environment?🤔 Considering that AI also makes mistakes and has different strengths depending on the #LLM behind it, this definitely makes sense. Until now, it has always been the human who has been the final quality gate, so what about another AI in the future?🤔 ❗️The advantage lies clearly in the scaling. A human is not even able to check all the measurements and to do so in a reasonable amount of time.😵💫❗️ So a clear yes?🤔 ❗️Definitely in terms of quality requirements, but from a commercial point of view 🤑 you have to check carefully whether the business case is right. The four-eyes principle in the AI environment can also quickly lead to a multiple of costs, as well as additional operational expenses, because of higher complexity.❗️ But the final question is, do we really want to give up completely? How are you seeing this? Human still in the loop or AI Four-eyes principle? https://lnkd.in/egkEc3rd #DesignTheFuture #AIfoureyesprinciple #AIquality

David Schlottman and Shelisa Brock provide insights into the impact and innovations of AI in the workplace and the possible regulations that are to come. As noted in the article, "The regulation of artificial intelligence is a new frontier. The way old laws might apply to this new technology is unclear. Fresh laws specifically regulating AI are also likely (and already exist in some places). Because so much is unknown about the technology and the effects of its use, there is undoubtedly first-adopter risk associated with the use of AI tools.” Check out the full article: https://lnkd.in/gwd9qGz7 #AI #innovation #artificialintelligence #AIregulation #futureofwork #JWinsights  

As AI rapidly advances, how do we assess whether these systems are truly effective, ethical, and safe? The short answer is doubling down on AI evaluation, but the landscape is becoming increasingly more complex.     AI evaluation, the functional testing and performance measurement of AI systems, used to be straightforward with models focusing on narrower tasks and set benchmarks. But with the emergence of #GenAI, AI models are now performing broader, open-ended tasks that require evaluations to not just measure accuracy, but also on dimensions like toxicity, fairness, and security.   Check out my new Forbes article for more on how AI evaluation is evolving, curious to hear your thoughts on this one!     https://bit.ly/3wX26tN   #AI #ArtificialIntelligence #RAI #ResponsibleAI #EthicalAI  

AI systems are rapidly evolving with the #GenAI revolution, and evaluation methods need to keep pace with the rising complexities to make sure these advancements are safe, effective, and ethical. While #AI evaluation, the functional testing and performance measurement of AI systems, used to be built on straightforward accuracy benchmarks, methods must now expand to cater to AI models that perform broader, open-ended tasks and include new dimensions like toxicity, fairness, and security. If you’re interested in learning more about this topic, you can read Sylvain Duranton’s new article in Forbes: https://bit.ly/3wX26tN #ResponsibleAI #RAI #EthicalAI

AI systems are rapidly evolving with the #GenAI revolution, and evaluation methods need to keep pace with the rising complexities to make sure these advancements are safe, effective, and ethical. While #AI evaluation, the functional testing and performance measurement of AI systems, used to be built on straightforward accuracy benchmarks, methods must now expand to cater to AI models that perform broader, open-ended tasks and include new dimensions like toxicity, fairness, and security. If you’re interested in learning more about this topic, you can read Sylvain Duranton’s new article in Forbes: https://bit.ly/3wX26tN #ResponsibleAI #RAI #EthicalAI

AI systems are rapidly evolving with the #GenAI revolution, and evaluation methods need to keep pace with the rising complexities to make sure these advancements are safe, effective, and ethical. While #AI evaluation, the functional testing and performance measurement of AI systems, used to be built on straightforward accuracy benchmarks, methods must now expand to cater to AI models that perform broader, open-ended tasks and include new dimensions like toxicity, fairness, and security. If you’re interested in learning more about this topic, you can read Sylvain Duranton’s new article in Forbes: https://bit.ly/3wX26tN #ResponsibleAI #RAI #EthicalAI

AI systems are rapidly evolving with the #GenAI revolution, and evaluation methods need to keep pace with the rising complexities to make sure these advancements are safe, effective, and ethical. While #AI evaluation, the functional testing and performance measurement of AI systems, used to be built on straightforward accuracy benchmarks, methods must now expand to cater to AI models that perform broader, open-ended tasks and include new dimensions like toxicity, fairness, and security. If you’re interested in learning more about this topic, you can read Sylvain Duranton’s new article in Forbes: https://bit.ly/3wX26tN #ResponsibleAI #RAI #EthicalAI

AI systems are rapidly evolving with the #GenAI revolution, and evaluation methods need to keep pace with the rising complexities to make sure these advancements are safe, effective, and ethical. While #AI evaluation, the functional testing and performance measurement of AI systems, used to be built on straightforward accuracy benchmarks, methods must now expand to cater to AI models that perform broader, open-ended tasks and include new dimensions like toxicity, fairness, and security. If you’re interested in learning more about this topic, you can read Sylvain Duranton’s new article in Forbes: https://bit.ly/3wX26tN #ResponsibleAI #RAI #EthicalAI

AI systems are rapidly evolving with the #GenAI revolution, and evaluation methods need to keep pace with the rising complexities to make sure these advancements are safe, effective, and ethical. While #AI evaluation, the functional testing and performance measurement of AI systems, used to be built on straightforward accuracy benchmarks, methods must now expand to cater to AI models that perform broader, open-ended tasks and include new dimensions like toxicity, fairness, and security. If you’re interested in learning more about this topic, you can read Sylvain Duranton’s new article in Forbes: https://bit.ly/3wX26tN #ResponsibleAI #RAI #EthicalAI

AI systems are rapidly evolving with the #GenAI revolution, and evaluation methods need to keep pace with the rising complexities to make sure these advancements are safe, effective, and ethical. While #AI evaluation, the functional testing and performance measurement of AI systems, used to be built on straightforward accuracy benchmarks, methods must now expand to cater to AI models that perform broader, open-ended tasks and include new dimensions like toxicity, fairness, and security. If you’re interested in learning more about this topic, you can read Sylvain Duranton’s new article in Forbes: https://bit.ly/3wX26tN #ResponsibleAI #RAI #EthicalAI