In this session, Seth Dobrin, IBM’s Former Chief AI Officer and newly appointed President of the Responsible AI Institute, and Jai Natarajan, VP of Strategic Business Development at iMerit share insights into the best practices for deploying artificial intelligence responsibly.
Watch this session to gain insights on:
- What is ‘Responsible AI’ in principle and in practice
- What leads to bias in AI and machine learning
- Ways to assess the risk of bias in AI systems
- Importance of human intelligence in deploying AI responsibly
- How implementing a Responsible AI program benefits the business
Here are 3 key takeaways from the session:
- Responsible AI goes beyond merely eliminating bias. Besides bias and fairness, it involves transparency, explainability, safety, security, consumer protection, and organizational preparedness.
- It is crucial to build AI models responsibly when they have the potential to impact someone’s health, wealth, and livelihood. Businesses should start focusing on Responsible AI the same way they do on security and privacy. It should be taken care of throughout the process, not just at the end.
- Responsible artificial intelligence is not only the right thing to do but it also makes good business sense. According to studies, leaders in AI agreed that responsible AI is resulting in better business outcomes. It has improved NPS scores and increased both top-line and bottom-line metrics.