Heymann argues that the larger the impact of a decision on an operation, the more important it is to ensure that the decision is not left completely to the computer. He believes that final accountability for decision-making in key areas needs to remain with management, especially when the cost of failure is high. He suggests that as we look for accountability in management decisions, we may want to think more about AI being defined as "amplified" intelligence as compared to purely "artificial."
Key takeaways:
- The article highlights four key areas of artificial intelligence: Machine Learning, Deep Learning, Natural Language Processing, and Cognitive Computing.
- While AI has significantly improved decision-making processes, the author argues that human intervention is still crucial, especially in areas with high risk or high impact on business results.
- AI systems should not be left to make decisions that have a significant impact on business operations. The larger the impact of a decision on an operation, the more important it is to ensure that the decision is not left completely to the computer.
- The author suggests that AI should be seen as "amplified" intelligence rather than purely "artificial," emphasizing the importance of human involvement and accountability in decision-making processes.