“Power and Prediction” discusses the potential of artificial intelligence (AI) to transform decision-making through improved prediction. The authors argue that AI can change the balance between rules and decisions, and that better predictions can give businesses a competitive advantage. However, the adoption of AI requires a systems mindset, as the entire system of decision-making and its processes may need to adjust. The authors also explore the potential for AI to change who holds power, as well as the challenges in building judgment associated with AI prediction.
Key Questions answered in this book
- How does AI prediction change the traditional decision-making process?
AI prediction changes the traditional decision-making process by reducing the cost and increasing the accuracy of prediction, which is a key input for any decision. Decision-making can be broken down into three components:
2. prediction, and
Data is the raw information that is available for the decision, prediction is the process of using data to forecast what will happen under different scenarios, and judgment is the process of determining the value or utility of different outcomes.
Traditionally, prediction was expensive and inaccurate, so humans relied more on their intuition and heuristics to make decisions. However, with the advent of AI, prediction becomes cheap and precise, so humans can use more data and scenarios to make better-informed decisions. AI also enables new types of decisions that were not possible before, such as personalized recommendations, dynamic pricing, and real-time optimization.
However, AI does not replace human judgment, which is still needed to evaluate the predictions and choose the best course of action. Human judgment also involves ethical, moral, and social considerations that AI cannot capture. Therefore, the optimal decision-making process in the age of AI is a combination of human and machine intelligence, where humans delegate prediction tasks to AI and focus on judgment tasks that require creativity, empathy, and wisdom.
- What are some potential benefits and drawbacks of decoupling prediction and judgment through AI adoption?
- AI can improve the accuracy and efficiency of prediction tasks, which are essential for decision-making in various domains.
- AI can enable new types of decisions that were not possible before, such as personalized recommendations, dynamic pricing, and real-time optimization.
- AI can reduce the cognitive load and bias of human decision-makers, who can focus on judgment tasks that require creativity, empathy, and wisdom.
- AI can enhance the value of human judgment, which is needed to evaluate the predictions and choose the best course of action based on ethical, moral, and social considerations.
- AI can increase the complexity and uncertainty of decision-making environments, which may require more data and judgment than available or feasible.
- AI can create new challenges and risks for data quality, security, and privacy, which may affect the reliability and validity of predictions.
- AI can shift the power and profits among decision-makers, intermediaries, and stakeholders, which may create conflicts and inequalities.
- AI can undermine the accountability and transparency of decision-making processes, which may erode trust and legitimacy.
- How can AI reduce bias and change power dynamics in organizations?
- AI can reduce bias by identifying and correcting the human biases that affect decision-making, such as affinity bias, confirmation bias, attribution bias, and the halo effect. AI can also help to diversify the data sources and algorithms that are used to generate predictions, and to monitor and report the potential issues and impacts of AI applications.
- AI can change power dynamics by enabling new types of decisions that were not possible before, such as personalized recommendations, dynamic pricing, and real-time optimization. AI can also shift the power and profits among decision-makers, intermediaries, and stakeholders, by creating new value propositions, business models, and competitive advantages.
- AI is a prediction technology that enhances decision-making by reducing uncertainty and increasing accuracy
- AI can transform industries by enabling new decisions, redesigning systems, and shifting power and profits.
- AI poses challenges and opportunities for innovation, regulation, ethics, and geopolitics
- A framework for understanding the economics of AI and its implications for the future of work, competition, and society.
- Helps to understand about the potential and pitfalls of AI, and how to leverage or protect their position in the coming AI disruptions
- We have entered a unique moment in history—The Between Times—after witnessing the power of this technology and before its widespread.
- Google CEO Sundar Pichai said that “AI is probably the most important thing humanity has ever worked on. I think of it as something more profound than electricity.” Google has already seen a benefit from AI. Many companies haven’t. A 2020 study by MIT’s Sloan Management Review and BCG, a global consultancy, found that just 11 percent of organizations reported significant financial benefits from AI.This wasn’t for lack of trying. Fifty-nine percent said they had an AI strategy. Fifty-seven percent had deployed or piloted AI solutions.
- AI Soluton Types
- AI POINT SOLUTION: A prediction is valuable as a point solution if it improves an existing decision and that decision can be made independently.
- AI APPLICATION SOLUTION: A prediction is valuable as an application solution if it enables a new decision or changes how a decision is made and that decision can be made independently.
- AI SYSTEM SOLUTION: A prediction is valuable as a system solution if it improves existing decisions or enables new decisions, but only if changes to how other decisions are made are implemented.
- The biggest increase in the adoption of AI is, if history is any guide, going to come from changes in systems. But such change will also be disruptive. By disruptive, we mean that it changes the roles of many people and companies within industries and, alongside those changes, causes shifts in power. That is, there are likely to be economic winners and losers, especially if system change occurs relatively quickly.
- System solutions are typically harder to implement than point solutions or application solutions because the AI-enhanced decision impacts other decisions in the system, However, in many cases, system solutions are likely to generate the greatest overall return to investments in AI
- When people think about AI, they think about the intelligent machines littered throughout popular culture. They think of helpful robots such as R2-D2 or WALL-E. They think of brilliant teammates such as Data from Star Trek or J.A.R.V.I.S. from Iron Man. They also think of those that turned rogue like HAL 9000 from 2001 or Ultron from The Avengers. Whatever their quirks or intentions, these representations of AI have one thing in common: no one disputes that they can think, reason, and have agency, just as we do.