The good, the bad & the ugly of AI

“AI applications are regularly being developed, but the exciting world of opportunities and possibilities includes other issues: privacy, ethics, energy consumption and liability. The discrepancy between what the developers create, what the customer buys, and what the government wants has increased the complexity bias. In this session, we will split the issues in the good, the bad and the ugly.

- The good: AI exceeds human intelligence when it gets to areas such as speed of processing, knowledge transfer, decision accuracy and operational modus. However, the human brain still wins on storage size, energy usage and parallel processing and many more points. We need to accept the fact that both forms of intelligence are good, but just different. What are those differences?

- The bad: A successful AI project isn’t only about data and technologies, but also processes and people. The bad refers to the typical mistakes made by a company. They can include incorrect training data to match the context, incorrect usage of learning algorithms and unconscious bias.  How can this be easily fixed?

- The ugly: Some issues aren’t mistakes, but purposeful approaches: generative AI (ChatGPT), fake news, autogenerated speech used to fake video speeches for instance, and more. It is a strong call for 'security by design' and protection for algorithms through legal frameworks, which are currently created. How ready are you as a company to embrace the future value and but also the risks of our current AI systems?