The Simple Economics of Artificial Intelligence
In “Prediction Machines,” economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb explore the advancement and growing use of artificial intelligence (AI). The key to AI is not actually intelligence but prediction. This text looks at the value of prediction and data, the importance of trade-offs, and the impact of AI in the workplace. Beneficial to business leaders, financial analysts, policy makers, and students, “Prediction Machines” offers insights, tools, and strategies on how to adapt businesses to the world’s ever-growing use of AI. Chapters 1 and 2 provide an introduction to the concept of prediction, discuss the economic cost of prediction machines, and describe how businesses can use prediction machines in their business strategy.
Five of the most common AI debates are listed blow. Apply the knowlege gained from the readings to critically examine how these questions affect society more broadly.
1. Will there still be jobs?
2. Will this generate more inequality?
3. Will few large companies control everything?
4. Will countries engage in race-to-the-bottom policy making and forfeit our privacy and security to give their domestic companies a competitive advantage?
5. Will the world end?
Requirements:
· There is no minimum or maximum required number of pages. Your analysis will be considered complete, if it addresses each of the 5 components outlined above.
· Use of proper APA formatting and citations. If supporting evidence from outside resources is used those must be properly cited. A minimum of 5 sources (excluding the course materials) from scholarly articles or business periodicals is required.
· Include your best critical thinking and analysis to arrive at your justification.
· Approach the assignment from the perspective of the senior executive leadership of the company.
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