學門類別
哈佛
- General Management
- Marketing
- Entrepreneurship
- International Business
- Accounting
- Finance
- Operations Management
- Strategy
- Human Resource Management
- Social Enterprise
- Business Ethics
- Organizational Behavior
- Information Technology
- Negotiation
- Business & Government Relations
- Service Management
- Sales
- Economics
- Teaching & the Case Method
最新個案
- A practical guide to SEC ï¬nancial reporting and disclosures for successful regulatory crowdfunding
- Quality shareholders versus transient investors: The alarming case of product recalls
- The Health Equity Accelerator at Boston Medical Center
- Monosha Biotech: Growth Challenges of a Social Enterprise Brand
- Assessing the Value of Unifying and De-duplicating Customer Data, Spreadsheet Supplement
- Building an AI First Snack Company: A Hands-on Generative AI Exercise, Data Supplement
- Building an AI First Snack Company: A Hands-on Generative AI Exercise
- Board Director Dilemmas: The Tradeoffs of Board Selection
- Barbie: Reviving a Cultural Icon at Mattel (Abridged)
- Happiness Capital: A Hundred-Year-Old Family Business's Quest to Create Happiness
A Better Way to Onboard AI
內容大綱
In a 2018 Workforce Institute survey of 3,000 managers across eight industrialized nations, the majority of respondents described artificial intelligence as a valuable productivity tool. But respondents to that survey also expressed fears that AI would take their jobs. They are not alone. The Guardian recently reported that in the UK "more than 6 million workers fear being replaced by machines." AI's advantages can be cast in a dark light: Why would humans be needed when machines can do a better job? To allay such fears, employers must set AI up to succeed rather than to fail. The authors draw on their own and others' research and consulting on AI and information systems implementation, along with organizational studies of innovation and work practices, to present a four-phase approach to implementing AI. It allows organizations to cultivate people's trust--a key condition for adoption--and to work toward a distributed cognitive system in which humans and artificial intelligence both continually improve.