Artificial Intelligence (AI) is revolutionizing every industry and discipline. However, it has become evident that AI cannot stand alone and requires the processing strengths of the human brain. Hybrid Intelligence (HI) systems combine the strengths of synthetic intelligence and the human brain and are proving to have the most significant potential.
Autonomy ≠ Superiority
Autonomous AI is a distant dream, and most AI systems require human involvement. Tesla’s Autopilot and Full Self-Driving (FSD) technologies, for instance, are not fully autonomous but require active driver supervision.
Why AI alone falls short
AI is wired differently than human intelligence, is good in narrowly defined domains, and needs to generalize better. Additionally, businesses need to learn how to integrate AI with humans, leading to failed implementations, antagonism against automation, and sunk costs.
The best of both bits of intelligence
Hybrid Intelligence (HI) recognizes the comparative advantages of AI and human intelligence and combines them to achieve better results and allow for mutual learning.
Classifying HI systems
HI systems can be classified into four categories based on the degree of decision-making openness and risk: Machine-Based AI Systems, Cyclic Machine-Human AI Systems, Sequential Machine-Human AI Systems, and Human-Based AI Systems.
Conclusion
AI is evolving, and new applications are being developed continually. As we uncover the limitations and deficiencies inherent in AI, reintroducing humans into the mix is a natural progression that leads to more robust, better overall system performance. Hybrid Intelligence (HI) provides a better way to harness the power of AI.
