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AI的追蹤錯誤:為了避免錯誤的警戒的有效利用

Tracking Mistakes in AI: Using Vigilance to Avoid Errors

出版商 Mercator Advisory Group, Inc. 商品編碼 963725
出版日期 內容資訊 英文 15 Pages, 3 Exhibits
商品交期: 最快1-2個工作天內
價格
AI的追蹤錯誤:為了避免錯誤的警戒的有效利用 Tracking Mistakes in AI: Using Vigilance to Avoid Errors
出版日期: 2020年10月08日內容資訊: 英文 15 Pages, 3 Exhibits
簡介

一般認為AI解決方案,會在不知不覺的情況下誤入歧途。人們認為應避免將AI應用於可能對社會產生重大負面影響的問題,其中一個例子,是社群網路的Facebook和You Tube等的產業計畫使用AI實施。

本報告提供全球AI的追蹤錯誤的相關調查,資料證明偏見的各種方法,解決方案,預防法等資訊。

本報告所包含的圖表的一部分:

亮點

  • 詞彙表
  • 資料證明偏見的各種方法
  • 解決方案
  • 預防法
  • 快捷方式的魅力和危險性
目錄

AI and machine learning can help FIs avoid risk - but they have risk of their own.

Mercator Advisory Group releases a new research report that examines the impact of hidden biases in ML and Artificial Intelligence-and how to avoid them.

AI models reflect existing biases if these biases are not explicitly eliminated by the data scientists developing the systems. Constant monitoring of the entire operation is required to detect these shifts. The remedy for such lack of focus is training.

Mercator Advisory Group's latest research Report, ‘Tracking Mistakes in AI: Use Vigilance to Avoid Errors’, discusses modes in which data models can deliver biased results, and the ways and means by which financial institutions (FIs) can correct for these biases.

"AI solutions can unwittingly go astray," comments Tim Sloane, the Report's author and director of Mercator Advisory Group's Emerging Technology Advisory Service and its VP Payments Innovation. "Applying AI to issues that can have large negative social consequences should be avoided. One example of this is using AI to implement the business plan of social networks Facebook, You Tube, and others, as presented in the documentary "The Social Dilemma." The documentary contends that social networks have optimized AI to drive advertising revenue at the expense of the individual and society. To drive revenue, social networks build psychographic models for each user to predict exactly which content will best engage that user."

This document contains 15 pages and 3 exhibits.

Companies mentioned in this research note include: The Federal Reserve, ProPublica, The Verge.

One of the exhibits included in this report:

Highlights of the research note include:

  • A glossary of terms
  • The various modes in which data can evidence biases
  • Solutions
  • Prophylactic methods
  • The appeal-and danger-of shortcuts