AI is cognitive automation, not cognitive autonomy

2023-10-09 · Source: Sparks in the Wind · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation · Depth: Intermediate, medium

Summary

The article reframes the understanding of AI, distinguishing it from popular science fiction narratives that portray it as artificial minds with autonomy. It categorizes AI into three types: Cognitive Automation, Cognitive Assistance, and Cognitive Autonomy. Cognitive Automation, which encompasses nearly all current AI, involves encoding human abstractions in software to automate tasks, either through explicit rules (symbolic AI) or by fitting models to labeled data (deep learning). Cognitive Assistance uses AI to augment human perception and decision-making, representing a significant future potential. Cognitive Autonomy, the creation of truly independent artificial minds, is deemed science fiction for the foreseeable future. Modern AI is primarily cognitive automation, focused on operationalizing human skills and concepts to make computers perform more tasks, rather than achieving true intelligence or autonomy.

Key takeaway

For AI Product Managers evaluating new applications, recognize that current AI excels at cognitive automation, not autonomy. Focus your development efforts on well-defined problems where human skills can be encoded or ample labeled data exists. Do not expect AI to spontaneously adapt to unforeseen situations or generate infinite returns without significant engineering investment, as it remains a tool for making computers perform more, not a self-aware entity.

Key insights

Modern AI is cognitive automation, not autonomous artificial minds, focused on operationalizing human skills.

Principles

• AI is about making computers do more, not replacing humans.
• Intelligence is adaptability to unknown unknowns, automation handles known unknowns.

In practice

• Integrate StableDiffusion into design products for cognitive assistance.
• Apply AI to problems with narrowly defined tasks or precise examples.

Topics

• Cognitive Automation
• Cognitive Autonomy
• Deep Learning
• Self-Driving Technology
• AI Paradigms

Best for: AI Engineer, Data Scientist, AI Product Manager

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Editorial summary, takeaway, and curation by AIssential. Original article published by Sparks in the Wind.