The AI Advantage Book Summary

Book Summary

15 min

Audio available

Brief Summary

Artificial Intelligence has the potential to completely transform work and society. Some job positions may be fully automated, while others will be augmented, and still, other new jobs will develop around the AI field. Organizations that are able to best reap the benefits of AI must develop a cognitive strategy for implementing the new technology. Transparency is essential for firms to address the potential challenges of AI, and governments should assume some responsibility to help mitigate the potential negative side effects, such as job loss, inequality, or fake news, that can come from AI adoption.

About the Author

Thomas H. Davenport is the President’s Distinguished Professor in Information Technology and Management at Babson College and the author of over twenty books. He is a Fellow of the MIT Initiative on the Digital Economy and a Senior Advisor to Deloitte Analytics. He is also the co-founder of the International Institute for Analytics.

Davenport’s work has previously appeared in The Wall Street Journal, Harvard Business Review, InformationWeek, the Financial Times, and Forbes. He was named one of the world’s Top 25 Consultants by Consulting magazine in 2003 and was listed by Poets and Quants and Fortune Magazine as one of the world's Top 50 Business School Professors in 2012.

Topics

Other

The AI Advantage Book Summary Preview

What You’ll Learn

Why it is essential for business leaders to develop cognitive strategies for implementing AI in their organizations
How adopting AI will improve analysis, make better predictions, and transform the workplace
The importance of transparency to help mitigate the potential negative organizational and societal side effects of AI.

Who Is This For

Business leaders who want to learn how to successfully implement AI technology in their organizations
Policymakers who are curious about the social and political implications of AI
Tech workers and early adopters who want to learn about the future of AI technology in the workplace

Key Insights

Artificial Intelligence encompasses a broad range of technologies and provides a wide range of possibilities that will completely transform work, government, and society. For now, it is mostly only big corporations and tech startups that have fully embraced the complex challenges and vast potential of AI.

Companies that are effectively able to utilize AI must first have a cognitive strategy in place to ensure they are assigning the new technology to the appropriate task, which will boost productivity and allow them to really reap the benefits of AI. Cognitive technologies can help companies automate tasks, analyze and model data, and make better predictions. Some job positions may eventually be fully automated, while some employees may only have their jobs augmented by AI technology, which will free them up to pursue more critical thinking, human decision-making tasks. Regardless, AI will eventually revolutionize the workplace, and governments and organizations should be prepared to help workers adjust to the changes. There are social, ethical, and technical implications to AI technology, so transparency is essential to help mitigate potential negative effects.

Artificial Intelligence Is No Longer A Thing of The Future

Artificial Intelligence no longer simply belongs to the realm of science fiction. It is a real technology that is being actively used today, in industries like academia, finance, and tech. Artificial Intelligence is also called “cognitive technologies,” because it is a technology by which machines are endowed with certain human capabilities. These capabilities can range from quick and simple tasks, like recognizing images, too many more complex tasks, like machine learning.

There are five main technologies that fall under the umbrella of Artificial Intelligence or AI. First, there is Statistical Machine Learning, in which machines can learn and identify patterns, and make inferences about relationships between the data. Neural Networks are a more complex type of machine learning, in which algorithms mimic the human brain by recognizing relationships, which they can then categorize and use to make predictions and assessments. Natural Language Processing is the process by which machines analyze and interpret the text and spoken language. A subset of this technology is Statistical Natural Language Processing, in which machine learning is used to analyze large chunks of language data and interpret the data to find statistically significant correlations. Another type of AI, Semantic Neural Language Processing, represents the semantics of an expression in logical form by analyzing language’s rules and relationships. Lastly, Robotics and Robotic Process Automation utilize robots to follow procedures to complete...