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October 24, 26
スライド概要
AIはすでに文書作成や翻訳、会計支援などの知的業務を行っています。ルールが明確でデータが豊富な仕事は自動化しやすく、会計や法務調査などが例です。一方、信頼や共感が必要な人間関係の仕事は置き換えが難しく、販売や看護、教育などが該当します。また、多くの組織が古いシステムに依存しており、技術的負債が残ります。AIが生み出す富の配分が重要な課題となります。
おすすめタグ:AI,Automation,Economic Inequality,Legacy Systems,Policy
261024 presented by jee54321 1
AI Is Already Doing Some Office Work AI is already helping with: Writing documents Translation Coding Accounting support Customer supporto 2
UK Perspective This is similar to how: Online banking reduced clerical work Self-checkouts reduced cashier work Digital services reduced paperwork AI is now automating parts of white-collar work. 3
Rule-Based Jobs Are Easier to Automate AI performs best when: Rules are clear Large amounts of data exist Results can be measured Examples: Accounting, Legal research Data processing Administration Software development 4
UK Perspective 5
Human-Centred Jobs Are Harder to Replace AI struggles with jobs involving: Trust Empathy Human relationships Physical presence Examples: Relationship-based sales Nurses, Care workers Teachers, Managers 6
UK Perspective 7
AI Is Strongest in "Closed Worlds" AI excels where: Rules are fixed Outcomes are measurable Environments are predictable Examples: Chess, Go, Shogi Mathematical proofs Software testing 8
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Legacy Computer Systems Still Matter Many organisations depend on old IT systems. Examples: Government databases Banking systems Insurance systems Manufacturing systems 10
UK Perspective This is similar to legacy systems still used by: NHS organisations Government departments Major banks These systems cannot be replaced quickly. 11
Technical Debt Is a Major Challengej Many systems contain decades of accumulated complexity. Problems include: Missing documentation Retired experts Outdated software Business rules known by few people Why It Matters AI may generate new systems effectively, but understanding old systems remains difficult. 12
AI Creates Wealth, Not Distribution AI can increase productivity and profits. However, AI does not decide: Who receives the profits How income is shared How taxes are collected Key Question Who owns the economic benefits created by AI? 13
Basic Income Is a Policy Question Basic Income is not primarily a technology issue. It is about: Taxation Welfare systems Social policy Income redistribution 14
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Productivity and Distribution Are Different A country can become more productive without everyone becoming richer. Higher productivity does not automatically mean: Higher wages Lower inequality Better living standards Key Idea Economic growth and income distribution are separate issues. 16
Main Takeaways Remember These Five Facts AI already performs some knowledge-based work. Rule-based jobs are easier to automate. Human-centred jobs are harder to replace. Legacy systems and technical debt will remain important. The biggest question is not AI itself, but how AI-generated wealth will be distributed. 17
Final Message The Central Question of the AI Age The future debate is not: “ “ "Can AI do the work?" The future debate is: “ “ "If AI creates most of the wealth, who receives the income?" This question may become one of the defining political and economic issues of the 21st century. 18
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