Will Humans-in-the-Loop Become Borgs? Merits and Pitfalls of Working with AI

We analyze how advice from an AI affects complementarities between humans and AI, in particular what humans know that an AI does not know: “unique human knowledge.” In a multi-method study consisting of an analytical model, experimental studies, and a simulation study, our main finding is that human choices converge toward similar responses improving individual accuracy. However, as overall individual accuracy of the group of humans improves, the individual unique human knowledge decreases. Based on this finding, we claim that humans interacting with AI behave like “Borgs,” that is, cyborg creatures with strong individual performance but no human individuality. We argue that the loss of unique human knowledge may lead to several undesirable outcomes in a host of human–AI decision environments. We demonstrate this harmful impact on the “wisdom of crowds.” Simulation results based on our experimental data suggest that groups of humans interacting with AI are far less effective as compared to human groups without AI assistance. We suggest mitigation techniques to create environments that can provide the best of both worlds (e.g., by personalizing AI advice). We show that such interventions perform well individually as well as in wisdom of crowds settings.

Complexity Aversion in Risky Choices and Valuations: Moderators and Possible Causes

In the age of digitalization and globalization, our decision environments have become increasingly complex. However, it remains unclear under what circumstances complexity affects risk taking. In two experiments (one with a representative sample), we go beyond the behavioral effects and provide a cognitive explanation for the impact of complexity on risk taking. Results show that complexity, defined as the number of outcomes of a risky lottery, decreased choice propensity in choices between two lotteries but had a smaller effect on valuations of individual lotteries. Importantly, participants who spent less time looking at the complex option in choices, were less affected by complexity. Thus, a dislike of cognitive effort can explain the effect of complexity and the difference between choice and valuation. The small effect of complexity on valuations could be explained by individual differences in cognitive ability. Together, we showed that the decision environment as well as individual differences affected the impact of complexity on risk taking and we discuss cognitive explanations for these phenomena.

Should you follow your gut? The impact of expertise on intuitive hiring decisions for complex jobs

As jobs become increasingly complex, organizations are challenged with finding effective ways to select and hire successful employees. The high level of uncertainty generally associated with hiring decisions is greater for complex jobs where it is difficult to identify the predictors of good job performance. Intuition research has found expert intuition to be effective in highly uncertain decision environments. However, most employment selection research dismisses the use of intuition and argues that even expert interviewers should not rely on their intuition. To bridge the two research streams, this paper addresses the research question: for complex jobs, can the intuition of expert decision-makers enhance the effectiveness of hiring decisions? The hypotheses were tested via an experimental study design using expert and nonexpert interviewer samples. The results demonstrate that, when recruiting for complex jobs, interviewer expertise does increase the quality of intuitive hiring decisions.

Logistics to the Rescue: An Elementary Introduction to Planning in Disaster Response Decision Environments

Logistics to the Rescue is a spreadsheet K–12 game designed as a platform to familiarize students with emergency logistics. In the game, students play the role of an emergency dispatcher, assigning locations to routes. The challenge presented is threefold. Students must serve as many locations as possible within a time-frame. Midroute, an additional set of locations whose requests may be inaccurate is revealed; these requests are termed unverified demand locations. Students must balance uncertainty and time while serving as many accurate locations as possible. Finally, they are interrupted to learn whether the unverified demand locations’ requests are accurate. The game serves as a pedagogical tool for simulating a postdisaster environment and it exposes the real-time implications of social media and the data it produces. It emphasizes the importance of social and ethical awareness in the field of emergency logistics by showcasing the consequences induced by civilians’ reliance on social media in times of crisis. In doing so, it highlights the expansive boundaries of engineering’s disciplines and content. It is our hope that Logistics to the Rescue will encourage students, especially girls, to pursue careers in science, technology, engineering, and mathematics by providing a distinctive narrative where engineering is viewed as creative/collaborative rather than technical/a-social.

The Evolution of China’s Sporting Diplomacy since 1949

The sporting diplomacy in China, as an integral part of China’s overall diplomacy, unswervingly upholds the fundamental foreign policy goal of preserving world peace and promoting common development since New China was founded. After adopting the policy of reform and opening, the sporting diplomacy in China has made historical achievements through intensive participation in international sporting competitions, extensive involvement in international sporting organizations, active hosting of mega sports events, and frequent engagement in cultural sporting exchanges with other countries. In the last decade, with a constant increase in China’s economy, cultural soft power and international influence of sports, China makes an all-round effort in the pursuit of major countrywide sporting diplomacy with Chinese characteristics. Currently, despite the severe challenges outside China, Beijing is making smooth preparations for the 2022 Winter Olympic and Paralympic Games, which embraces another milestone in the diplomacy of sport in China. This paper analyzes decision environments, goals, actions and defining features of China’s sporting diplomacy in different periods and follows on to summarize practical experiences in the development of the sporting diplomacy in China. The paper shows that the resounding success of China’s sporting diplomacy can be attributed to its commitment to serving the country’s diplomatic strategy and core interests, its commitment to following the Chinese path of sporting diplomacy, and its commitment to the traditional Chinese value of peaceful development. Finally, emerging issues and promotion strategies are presented.

Memory patterns for choice adaptation in dynamic environments

An important aspect of making good decisions is the ability to adapt to changes in the values of available options. Research suggests that we are poor at changing behavior and adapting our choices successfully. This work contributes to clarifying the role of memory on learning and successful adaptation to changing decision environments. We test the effects of the direction of change and the type of feedback using a decisions from experience binary choice task, where individuals learn the outcomes and their associated probabilities from feedback received after selecting between available choice options. The results revealed a robust effect of the direction of change: risk that becomes more rewarding over time is harder to detect than risk that becomes less rewarding over time; and even with full information about the outcomes of choice options people showed sub-optimal adaptation to change. We rely on three distinct computational models to interpret the role of memory on learning and adaptation. The distributions of individual model parameters were analyzed in relation to participants' ability to successfully adapt to the changing conditions of the various decision environments. Consistent across the three models and two distinct data sets (our experimental data and other researchers' data), results revealed the value of recency as an individual memory component for choice adaptation. Individuals relying more on recent experiences were more successful at adapting to change, regardless of the direction of change. We explain the value and limitations of these findings as well as opportunities for future research.

The Strategy Aggregation Effect in Judgment

Predicting a criterion that is probabilistically related to pieces of information, or cues, is a paradigmatic judgment task that has been investigated both, in research trying to identify the individual judgment and decision making strategies people use, and in the wisdom-of-crowds literature where the focus is on how aggregation can improve accuracy. I combine these two lines of research to investigate how the performance of individual and aggregated linear strategies are affected by different environmental and group aggregation factors and how performance differences between individual and aggregated linear strategies can be understood in a unified framework. I show that constrained linear strategies are more accurate for individual judgments, but when these judgments are averaged, an unconstrained linear strategy is more accurate. This strategy aggregation effect can be understood by analyzing a decomposition of the mean squared error into bias, variance, and covariance. Because of their lower bias but higher variance, unconstrained linear strategies perform worse for individual judgments, but better for averaged judgments where aggregation minimizes variance. In simulations with artificial and real environments, I further show that this aggregation effect does not occur if there are correlations between individual judgments. Here, constrained linear strategies always outperform an unconstrained linear strategy, because the larger covariance component of the unconstrained linear strategy outweighs its lower bias. I end with real-world implications of the results for cognitive strategies and decision environments in group and organizational settings.

Modeling Ground Firefighting Resource Activities to Manage Risk Given Uncertain Weather

Wildland firefighting requires managers to make decisions in complex decision environments that hold many uncertainties; these decisions need to be adapted dynamically over time as fire behavior evolves. Models used in firefighting decisions should also have the capability to adapt to changing conditions. In this paper, detailed line construction constraints are presented for use with a stochastic mixed integer fire growth and behavior program. These constraints allow suppression actions to interact dynamically with stochastic predicted fire behavior and account for many of the detailed line construction considerations. Such considerations include spatial restrictions for fire crew travel and operations. Crew safety is also addressed; crews must keep a variable safety buffer between themselves and the fire. Fireline quality issues are accounted for by comparing control line capacity with fireline intensity to determine when a fireline will hold. The model assumes crews may work at varying production rates throughout their shifts, providing flexibility to fit work assignments with the predicted fire behavior. Nonanticipativity is enforced to ensure solutions are feasible for all modeled weather scenarios. Test cases demonstrate the model’s utility and capability on a raster landscape.