One of the most important ethical issues raised or exacerbated by AI concerns data: how is it collected, to whom does it belong, what do individuals and businesses need to know, and what is data citizenship? Participants will gain an accurate (but non-math, non-engineering) understanding of what AI can and cannot do with data, what ethical issues arise, and what the practices are that businesses and individuals should utilize.
Capability to understand the ethical issues that arise in businesses that use AI and data, and to participate responsibly in corporate decision-making when appropriate. Hour 1 – Participants will be able to identify the 2 tasks at which AI excels (classifying and predicting). They will be able to articulate what a neural network is, what machine learning is, and the difference between training and real-world data. Hour 2 – Participants will be able to articulate the major ways data is collected, the uses to which it is currently put by businesses and government, identify the major ethical challenges posed by artificial intelligence: data privacy, transparency, bias.
Hour 1: What Is AI? What Is Data? * Case 1: China’s use of phone apps to reduce transmission of Coronavirus. (see https://www.nytimes.com/2020/05/26/technology/china-coronavirus-surveillance.html?searchResultPosition=1 )
Hour 2: Data Privacy, Data Brokers, And What You Should Do Learning objectives. By the end of this hour, participants will be able to articulate the major ways data is collected, the uses to which it is currently put by businesses and government, identify the major ethical challenges posed by artificial intelligence: data privacy, transparency, bias.
* Case study 1: Amazon’s AI recruiting tool
* Case study 2: 23andMe: Who Sees What?
Anyone looking to understand the ethical issues that arise in businesses that use AI and data, and to participate responsibly in corporate decision-making when appropriate.
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