We spent an enthralling 60-minute session on how Artificial Intelligence (AI) understands reality, according to the latest joint theory of computer scientists and philosophers. This introductory post on Artificial Intelligence will give you more insights on the topic, as well as on the speaker – Prof. Dan Cautiș. Join the AI community around the talk on our Facebook event page.
At the heart of our FUTURE HORIZONS event, Prof. Dan Cautiș from Georgetown University talked about the philosophical considerations in artificial intelligence, machine learning and statistical networks, tackling some controversial topics such as correlation vs causation.
This discussion proved yet again how important philosophy is to science in general and to machine learning in particular, how ignoring philosophical analysis could create erroneous results even using correct algorithms and how a joint team of researchers (computer science and philosophers) was able to bring new and important discoveries in the epistemology of causation that would have been impossible had they worked independently.
Key takeaways:
- How structural causal discovery works in large systems of information and events
- New grounds in how AI understands reality and handles uncertainty
- Practical implications in robotics, medical diagnostics expert systems, drug discovery, social sciences studies, manufacturing quality improvements.
