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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
AI-at-Scale Hinges on Gaining a 'Social License'
內容大綱
For AI deployments to succeed, the systems must be trusted and accepted by those who use their input and those who are affected by the decisions these systems make or support. That means being accountable for the use and outputs of AI technologies, and transparently communicating both the benefits and drawbacks to all stakeholders. The authors describe the three sources of stakeholders' trust in artificial intelligence and suggest four steps companies can take to earn that trust.