Cassie Kozyrkov, Former Chief Decision Scientist at Google, discusses the limitations of data and the need to put a face on technology. They explore the evolution of prompts, the fallacy of data as god, and the distinction between thinking and thunking in different professions. They also emphasize the importance of collaboration, measuring and evaluating technology, and responsible AI use.
Business leaders need to be educated in decision making surrounding technology to make better decisions and be held accountable.
Creating a seamless user experience with AI involves demystifying it and making it more transparent and accountable.
Recognizing the value of both thinking and thunking tasks is essential for fostering innovation and supporting diverse skills and decision-making.
Deep dives
The Importance of Educated Decision Makers
The podcast episode emphasizes the importance of having business leaders who are educated in decision making surrounding technology, specifically in the field of conversational AI. The guest, Cassie Kozerkov, highlights the need for leaders who are knowledgeable about technology so that they can make better decisions and be held accountable by consumers. The podcast also discusses the significance of broad education to ensure that business leaders and the general public are well-informed about technology and can understand what constitutes a good decision in relation to it.
Demystifying AI and Putting a Responsible Face on Technology
The conversation with Cassie Kozerkov dives into the need to demystify AI and make technology more seamless for users. It is important for users to be able to interact with AI without being fully aware of its presence and without needing to understand the technical aspects behind it. The focus is on creating a user experience that is seamless, correct, and doesn't require the user to think about the AI working in the background. The podcast also emphasizes the importance of putting a responsible face on technology and not relying solely on the magic of AI, but rather making it more transparent and accountable to users.
The Competing Priorities of Thunking and Thinking
The podcast delves into the idea of competing priorities between thunking and thinking. Thunking refers to the non-thinking, mindless tasks that often dominate work. The discussion raises concerns about the overemphasis on productivity and maximizing thunking tasks in the workplace. It highlights the need to shift the focus towards thinking tasks, which involve creativity, original thought, and problem-solving. The podcast suggests that by letting go of the obsession with maximizing thunking, there may be room for individuals to engage in deep thinking and come up with innovative ideas. It also raises questions about how technology and algorithms, such as likes on social media platforms, can impact productivity and creativity by promoting certain behaviors and limiting diversity of thought.
The Importance of Both Thinking and Thunking in Work
Every job has two components: thinking and thunking. Thinking involves the creative and intellectual aspects of a job, while thunking refers to the routine or repetitive tasks. Even in seemingly intellectual fields like science, there is still a lot of mundane work involved. The history of management and productivity has focused more on measuring and managing thunking tasks, as they are easier to observe and quantify. However, this narrow focus on productivity undermines the value of thinking and creativity. It is important to recognize that both thinking and thunking are essential components of any job, and they should be given equal attention and recognition.
Competition, Collaboration, and the Redesign of Metrics
Competition and the measurement of performance have been ingrained in education and business environments. However, the concept of competition as a motivator and measurement tool is often flawed. Competition based on simple-minded and monolithic metrics, such as standardized test scores or credit scores, may not accurately reflect individual capabilities or potential. Moreover, these metrics can lead to unintended consequences and a lack of innovation and collaboration. Instead of solely focusing on competition, there should be a shift towards fostering collaboration and designing systems with customized objectives. By recognizing the value of variety, individual strengths, and collaboration, we can create better environments that support diverse skills and decision-making.
Robb and Josh welcome Cassie Kozyrkov, Google's First Chief Decision Scientist, for a conversation about the limitations of data and the need to put a face on technology. Cassie is now CEO of Data Scientific and helped shape the technology all around us, and this far-ranging discussion of conversational AI examines the composition of the technologies that go into artificial intelligence, the ways we can use technology to help people make better quality decisions, and why we should look for opportunities to automate "thunking" moments.
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