#7 How AI will change the world by 2030 with Eric Redmond (Nike)

2021-11-30 · Source: AI LITERACY - A Podcast about Artificial Intelligence · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Robotics & Autonomous Systems, Emerging Technologies & Innovation · Depth: Intermediate, extended

Summary

Eric Redmond, Director of Nike's Tech Innovation Office and author of "Deep Tech," discusses how artificial intelligence and six other converging technologies will reshape the world by 2030. He emphasizes that AI is the most disruptive and general-purpose technology, impacting industries from mental labor like programming to physical tasks in agriculture. Redmond highlights the concept of "cobots" – collaborative robots that work alongside humans, improving efficiency and accuracy, such as in medical diagnostics. He categorizes AI into supervised, unsupervised, and reinforcement learning, explaining their distinct applications like image classification, fraud detection, and goal-oriented task learning. Redmond also addresses barriers to AI adoption, noting that while ideas are plentiful, the necessary data infrastructure and explainability remain challenges. He advocates for tech literacy, urging individuals to embrace technology to automate mundane tasks and enhance creativity.

Key takeaway

For executives and professionals navigating digital transformation, understanding the "Deep Tech" landscape, particularly AI's varied applications and limitations, is critical. Your organization should prioritize building robust data infrastructure to support AI initiatives and invest in continuous tech literacy for your workforce. Embrace collaborative AI (cobots) to augment human capabilities, rather than solely focusing on full automation, to drive both efficiency and improved outcomes.

Key insights

Converging deep technologies, especially AI, will profoundly transform industries and daily life by 2030.

Principles

• AI is the most general-purpose technology.
• Cobots enhance human performance and accuracy.
• Tech literacy is crucial for future job market readiness.

Method

AI applications are categorized into supervised learning (labeled data), unsupervised learning (anomaly detection), and reinforcement learning (goal-driven action without explicit instruction).

In practice

• Explore AI to automate mundane tasks.
• Consider quantum computing for future programming skills.
• Develop a metaverse strategy for major brands.

Topics

• Deep Tech
• AI Applications
• Machine Learning Paradigms
• Cobots
• AI Explainability

Best for: Executive, AI Product Manager, Software Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI LITERACY - A Podcast about Artificial Intelligence.