Deepening Decision-making Skills: Can They Be Practiced?
Chess grandmasters are often viewed as the embodiment of long-term thinking. With their exceptional ability to plan ahead by several steps, they are recognized as skilled decision-makers who can anticipate the consequences of their moves. But can others learn this skill with practice?
A team of cognitive scientists from the New York University Center for Neural Sciences has developed a novel computational model that delves into our ability to plan for future events. The model sheds light on the factors that influence decision-making and elucidates how planning skills can be honed through practice. The study, which was published in the journal Nature, focussed on the depth of planning, which refers to the number of steps an individual can consider as part of their planning process.
The ability to plan multiple steps into the future has long been established as a hallmark of human intelligence. However, it is less clear whether skilled decision-makers plan further ahead than novices. This is partially due to measurement methods, such as board game experiments, which do not provide reliable depth of planning estimations. In light of this, the authors of the journal article decided to create a video game version of tic-tac-toe, which requires players to plan deeply. The scientists then designed a computational model that is based on AI principles to understand the moves people make when strategizing in the game. “In this computational model, players build a ‘decision tree’ in their heads in the same way you might plan multiple possible scenarios for a complex travel itinerary,” explains Wei Ji Ma, a professor of neuroscience and psychology at the University of New York and lead author of the article. The research concludes that even a relatively modest amount of practice can enhance an individual’s depth of planning.
Validation and insights
To test the accuracy of this novel model, the researchers conducted behavioral experiments with human participants. They observed how the players planned their moves in various scenarios while testing their memory and gaming experiences. They also ran a Turing test experiment, where observers were asked to determine whether the movement sequences were generated by the model or human players. The observers were correct only about half of the time, which suggests the model’s decision-making abilities are similar to that of humans.
The study’s results showed that better planning results from the ability to recognize patterns accurately and more quickly, underlining the benefits of practice and experience. Cognitive skills can be improved in adulthood through practice, and this opens up new research avenues. For example, researchers can use these methods to analyze the development of planning skills in children or to study whether these skills can be sustained in older adults.
Skills required for effective decision-making
The study explains that planning skills can be interpreted as “search skills” that involve discovering hidden information by exploring several alternative future scenarios. According to a Harvard Business Review article by Grant Ackerman and others, effective decision-making involves three core skills: 1) the ability to understand the business; 2) the skill to weigh evidence objectively; and 3) the skill to examine alternatives exhaustively. These skills are all associated with the ability to search effectively.
For example, understanding the business means understanding the rules of the “game,” such as the constraints and opportunities that exist. This involves searching for information about the business, its competitors, and its environment. Weighing evidence objectively involves searching for valid evidence from multiple sources and generating alternative explanations for the evidence. “To search for alternatives exhaustively,” the authors explain, “you need to generate possible reasons why a choice might be less successful and search for data that undermines each reason.”
The study aligns with the notion that effective decision-makers need to develop deep search skills to anticipate multiple future scenarios and generate several alternative explanations for the evidence.
How to develop deep search skills
The key insight from the study is that deep search skills can be developed with practice. The authors recommend that individuals engage in various activities that can help improve their search skills, including playing strategy board games such as chess, reading complex material, and participating in team brainstorming sessions. These activities require individuals to think about future scenarios as well as to examine alternatives. Practicing these skills on a regular basis can enhance an individual’s cognitive abilities, allowing them to develop better decision-making skills.
Emerging research also indicates that playing various genres of video games can help develop certain cognitive skills. One study conducted by the University of Rochester found that playing action games can improve an individual’s contrast sensitivity function, essential for driving in the fog or reading fine print. Another study by Simon Fraser University demonstrated that playing video games can help counter the effects of aging by enhancing the cognitive functioning of older adults.
Conclusion
The study reveals that effective planning involves deep search skills that enable individuals to generate multiple future scenarios and alternatives. The research demonstrates that planning skills can be developed with practice, which offers new avenues for research in improving decision-making skills in individuals of all ages. People can improve their planning skills by engaging in activities that require deep search skills, such as reading complex material, playing strategy board games, and participating in brainstorming sessions. Video games can also help by enhancing cognitive functioning. Therefore, an investment in resources for practicing these key search skills can result in improved decision-making across all areas of life.
Summary:
The New York University Center for Neural Sciences’ cognitive scientists created a computational model that builds a person’s “decision tree” in the same way they might plan a complex travel itinerary. Using this model, the team found that even a modest amount of practice can enhance an individual’s depth of planning. Better planning is caused by the ability to recognize patterns swiftly and accurately, indicating that skill can be improved through practice and experience. Deep search skills are vital in effective decision-making by anticipating multiple future scenarios, examining alternatives exhaustively, and weighing evidence objectively. Engaging in activities like strategy board games, reading complex material and participating in brainstorming sessions can help develop these skills. Emerging research demonstrates that video games can enhance cognitive functioning, counteracting the effects of aging. An investment in resources for practicing these key search skills in individuals can result in improved decision-making across all areas of life.
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Chess grandmasters are often presented as the epitome of long-term thinking. But can others, with a modest amount of practice, learn think later?
Addressing this question, a team of cognitive scientists has created a computational model that reveals our ability to plan for future events. The work improves our understanding of the factors that affect decision making and shows how we can improve our planning skills through practice.
The research, conducted by scientists at New York University’s Center for Neural Sciences and published in the journal Naturefocuses on the role of “depth of planning” (the number of steps an individual thinks into the future) in decision making.
“While artificial intelligence has made impressive progress in solving complex planning problems, much less is known about the nature and depth of planning in people,” explains Wei Ji Ma, a professor of neuroscience and psychology at the University of New York and lead author of the article. “Our work adds to this body of knowledge by showing that even a relatively modest amount of practice can improve planning depth.”
It has long been established that a hallmark of human intelligence is the ability to plan multiple steps into the future. However, it is less clear whether or not skilled decision makers plan further steps forward than novice ones. This is because methods for measuring this aptitude (eg, board game experiments) have notable shortcomings, in part because they do not reliably estimate depth of planning.
He Nature The authors of the article had people play a relatively simple game, a more sophisticated version of tic-tac-toe, which still required players to plan deeply (ie several steps ahead). Then, in order to accurately understand what is going on in people’s minds as they think about their next move in this game, the authors designed a computer model based on AI principles. The model allows them to describe and subsequently predict the moves people make when faced with new situations in the game.
“In this computational model, players build a ‘decision tree’ in their heads in the same way you might plan multiple possible scenarios for a complex travel itinerary,” Ma explains.
Here, their calculations showed that human behavior can be captured using a computational cognitive model based on a heuristic search algorithm, one that maps out a sequence of promising moves for both players.
To validate the model, the researchers conducted a series of behavioral experiments with human participants. Specifically, they tracked how players planned their moves in different scenarios while testing their memory and ability to learn and piece together their gaming experiences. In addition, the team ran a Turing test experiment in which observers, who had played the game before, were asked to determine whether the movement sequences they witnessed were generated by the model or by human players. These observers were able to make the correct distinction only about half the time, suggesting that the model makes decisions similar to what a human would. Several of these experiments can be played online by visiting Ma’s lab website.
Overall, their results showed that better planning is driven by the ability to recognize patterns more accurately and in less time, results that point to the benefits of practice and experience.
“It is known that cognitive skills can be improved in adulthood through practice,” Ma observes. “These findings show that even a relatively modest amount of practice can improve the depth of planning. This opens up new avenues of research. For example, we can use these methods to study the development of planning skills in children, or assess whether planning skills can be retained into old age.Of course, it is also crucial that we connect planning in the laboratory with planning in real life”.
The other authors on the paper are: Bas van Opheusden, a New York University doctoral student at the time of the study and now a research scientist on Generally Intelligent; Ionatan Kuperwajs, a New York University doctoral student; Gianni Galbiati, a researcher at NYU at the time of the study and now director of research and development at Vidrovr; Zahy Bnaya, a postdoctoral researcher at the NYU Center for Neural Sciences; and Yunqi Li, a New York University researcher at the time of the study and now a PhD student at Stanford University.
The research was supported by grants from the National Science Foundation (IIS-1344256, DGE1839302).
https://www.sciencedaily.com/releases/2023/05/230531150112.htm
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