scholarly journals A Vague Theory of Choice over Time

2006 ◽  
Vol 6 (1) ◽  
Author(s):  
Paola Manzini ◽  
Marco Mariotti
Keyword(s):  
Decision Makers ◽  
Time Preferences ◽  
Preference Reversal ◽  
Novel Approach ◽  
Human Decision ◽  
Future Events ◽  
Over Time

We propose a novel approach to modelling time preferences, based on a cognitive shortcoming of human decision makers: the perception of future events becomes increasingly `blurred' as the events are pushed further in time. Our model explains behavioural `anomalies' such as preference reversal and cyclical choice.

scholarly journals Human-Centric Justification of Machine Learning Predictions

2017 ◽  
Author(s):  
Or Biran ◽  
Kathleen McKeown
Keyword(s):  
Machine Learning ◽  
Domain Knowledge ◽  
Decision Makers ◽  
Decision Making Process ◽  
Human Reasoning ◽  
Learning Models ◽  
Language Generation ◽  
Novel Approach ◽  
Human Decision ◽  
Machine Learning Models

Human decision makers in many domains can make use of predictions made by machine learning models in their decision making process, but the usability of these predictions is limited if the human is unable to justify his or her trust in the prediction. We propose a novel approach to producing justifications that is geared towards users without machine learning expertise, focusing on domain knowledge and on human reasoning, and utilizing natural language generation. Through a task-based experiment, we show that our approach significantly helps humans to correctly decide whether or not predictions are accurate, and significantly increases their satisfaction with the justification.

People versus Policies: Decision-makers have divergent preferences for decisions about individuals and equivalent policies that affect individuals

2020 ◽  
Author(s):  
David Mauricio Munguia Gomez ◽  
Emma Levine
Keyword(s):  
Real World ◽  
College Admissions ◽  
Decision Makers ◽  
Preference Reversal ◽  
Lay People ◽  
Admissions Officers ◽  
New Type ◽  
Selection Policies

Across nine main studies (N = 7,024) and nine supplemental studies (N = 3,279), we find that people make systematically different choices when choosing between individuals and choosing between equivalent policies that affect individuals. In college admissions and workplace hiring contexts, we randomly assigned participants to select one of two individuals or choose one of two selection policies. People were significantly more likely to choose a policy that would favor a disadvantaged candidate over a candidate with objectively higher achievements than they were to favor a specific disadvantaged candidate over a specific candidate with objectively higher achievements. We document these divergent choices among admissions officers, working professionals, and lay people, using both within-subject and between-subject designs, and across a range of stimuli and decision contexts. We find evidence that these choices diverge because thinking about policies causes people to rely more on their values and less on the objective attributes of the options presented, which overall, leads more people to favor disadvantaged candidates in selection contexts. This research documents a new type of preference reversal in important, real-world decision contexts, and has practical and theoretical implications for understanding why our choices so frequently violate our espoused policies.

Forecasting Interconnections in International Housing Markets: Evidence from the Dynamic Model Averaging Approach

2020 ◽  
Vol 42 (1) ◽  
pp. 37-103
Author(s):  
Hardik A. Marfatia
Keyword(s):  
Dynamic Model ◽  
Model Averaging ◽  
Housing Markets ◽  
The United States ◽  
Forecasting Model ◽  
Change Over Time ◽  
The United Kingdom ◽  
Novel Approach ◽  
Dynamic Model Averaging ◽  
Over Time

In this paper, I undertake a novel approach to uncover the forecasting interconnections in the international housing markets. Using a dynamic model averaging framework that allows both the coefficients and the entire forecasting model to dynamically change over time, I uncover the intertwined forecasting relationships in 23 leading international housing markets. The evidence suggests significant forecasting interconnections in these markets. However, no country holds a constant forecasting advantage, including the United States and the United Kingdom, although the U.S. housing market's predictive power has increased over time. Evidence also suggests that allowing the forecasting model to change is more important than allowing the coefficients to change over time.

scholarly journals On the Juridical Relevance of the Phenomenological Notion of Person in Max Scheler and Edith Stein

2021 ◽  
Author(s):  
Francesco Galofaro
Keyword(s):  
Artificial Intelligence ◽  
Edmund Husserl ◽  
Phenomenological Analysis ◽  
Machine Learning Algorithms ◽  
Decision Makers ◽  
Edith Stein ◽  
Max Scheler ◽  
Human Decision ◽  
The Difference ◽  
Social Units

AbstractThe paper presents a semiotic interpretation of the phenomenological debate on the notion of person, focusing in particular on Edmund Husserl, Max Scheler, and Edith Stein. The semiotic interpretation lets us identify the categories that orient the debate: collective/individual and subject/object. As we will see, the phenomenological analysis of the relation between person and social units such as the community, the association, and the mass shows similarities to contemporary socio-semiotic models. The difference between community, association, and mass provides an explanation for the establishment of legal systems. The notion of person we inherit from phenomenology can also be useful in facing juridical problems raised by the use of non-human decision-makers such as machine learning algorithms and artificial intelligence applications.

Who’s making the decisions? How managers can harness artificial intelligence and remain in charge

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pooya Tabesh
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Big Data ◽  
Digital Transformation ◽  
Decision Processes ◽  
Decision Makers ◽  
Content Type ◽  
Human Decision ◽  
Practical Implications

Purpose While it is evident that the introduction of machine learning and the availability of big data have revolutionized various organizational operations and processes, existing academic and practitioner research within decision process literature has mostly ignored the nuances of these influences on human decision-making. Building on existing research in this area, this paper aims to define these concepts from a decision-making perspective and elaborates on the influences of these emerging technologies on human analytical and intuitive decision-making processes. Design/methodology/approach The authors first provide a holistic understanding of important drivers of digital transformation. The authors then conceptualize the impact that analytics tools built on artificial intelligence (AI) and big data have on intuitive and analytical human decision processes in organizations. Findings The authors discuss similarities and differences between machine learning and two human decision processes, namely, analysis and intuition. While it is difficult to jump to any conclusions about the future of machine learning, human decision-makers seem to continue to monopolize the majority of intuitive decision tasks, which will help them keep the upper hand (vis-à-vis machines), at least in the near future. Research limitations/implications The work contributes to research on rational (analytical) and intuitive processes of decision-making at the individual, group and organization levels by theorizing about the way these processes are influenced by advanced AI algorithms such as machine learning. Practical implications Decisions are building blocks of organizational success. Therefore, a better understanding of the way human decision processes can be impacted by advanced technologies will prepare managers to better use these technologies and make better decisions. By clarifying the boundaries/overlaps among concepts such as AI, machine learning and big data, the authors contribute to their successful adoption by business practitioners. Social implications The work suggests that human decision-makers will not be replaced by machines if they continue to invest in what they do best: critical thinking, intuitive analysis and creative problem-solving. Originality/value The work elaborates on important drivers of digital transformation from a decision-making perspective and discusses their practical implications for managers.

scholarly journals Persistent Wrinkles and Folds of Clothes

2011 ◽  
Vol 10 (1) ◽  
pp. 61-66 ◽  
Author(s):  
Byung-Cheol Kim ◽  
Seungwoo Oh ◽  
Kwangyun Wohn
Keyword(s):  
Energy Loss ◽  
Energy Model ◽  
Stiffness Coefficients ◽  
Novel Approach ◽  
Linear Buckling ◽  
Non Linear ◽  
And Behavior ◽  
Rest Posture ◽  
Over Time

We present a novel approach to woven-cloth simu-lation in order to generate persistent wrinkles and folds. For a couple of decades, our community has identified and mimicked non-linear buckling of cloth based on the mechanical measure-ment of cloth. It has, however, scarcely paid attention to another important aspect of the measurement, the hysteresis of cloth be-haviors, which is the lag of the amount of forces between stress and relaxation. Our interpretation of the measurement indicates that persistent wrinkles and folds develop in part from the hyste-resis of cloth and its associated energy loss. Thus, we establish an adaptive energy model which takes stiffness coefficients and rest posture values not as constants but as variables over time and behavior. As stiffness coefficients and rest posture values change in proportion to the amount of the energy loss, they appear as persistent wrinkles and folds. Consequently, the clothes simulated by our method bring more realism with respect to visual identi-fication for past behaviors of cloth.

Proximate Mechanisms of Individual Decision-Making Behavior

2016 ◽  
Author(s):  
Paul W. Glimcher
Keyword(s):  
Twentieth Century ◽  
Large Scale ◽  
Resource Constraints ◽  
Empirical Work ◽  
Decision Makers ◽  
Decision Variable ◽  
Computational Resource ◽  
Human Decision ◽  
Holistic Theory ◽  
Decision Making Behavior

In the early twentieth century, neoclassical economic theorists began to explore mathematical models of maximization. The theories of human behavior that they produced explored how optimal human agents, who were subject to no internal computational resource constraints of any kind, should make choices. During the second half of the twentieth century, empirical work laid bare the limitations of this approach. Human decision makers were often observed to fail to achieve maximization in domains ranging from health to happiness to wealth. Psychologists responded to these failures by largely abandoning holistic theory in favor of large-scale multi-parameter models that retained many of the key features of the earlier models. Over the last two decades, scholars combining neurobiology, psychology, economics, and evolutionary approaches have begun to examine alternative theoretical approaches. Their data suggest explanations for some of the failures of neoclassical approaches and revealed new theoretical avenues for exploration. While neurobiologists have largely validated the economic and psychological assumption that decision makers compute and represent a single-decision variable for every option considered during choice, their data also make clear that the human brain faces severe computational resource constraints which force it to rely on very specific modular approaches to the processes of valuation and choice.

Thinking Systemically About Security and Resilience in an Era of Cybered Conflict

2019 ◽  
pp. 44-59
Author(s):  
Peter Dombrowski ◽  
Chris C. Demchak
Keyword(s):  
International System ◽  
Well Being ◽  
Decision Makers ◽  
Systemic Approach ◽  
Economic Systems ◽  
The World ◽  
Peace And War ◽  
Over Time ◽  
Civil Societies

The international system now depends on cyberspace, a global ‘substrate' of massive, complex, insecurely designed networks providing systemic advantages to masses of predators and adversaries. States today face an unprecedented spectrum of ‘cybered conflict' between peace and war with growing existential implications. Their piecemeal searches for defensible jurisdictions are creating a rising Cyber Westphalian world crisscrossed with gateways, holes, national cyber forces, and often partial, uncoordinated, or vague strategies. Over time, the world will have robust, midlevel, and poor cyber powers, with the first tier coercing the others and dominating the rules of exchange. Democratic civil societies are not guaranteed to be robust. For acceptable future societal well-being in a deceptive and opaque cybered world, decision-makers need a systemic approach based on the logic of complex socio-technical-economic systems (STES) to create the systemic resilience and disruption capacities across shareable (across allies/sectors) secure architectures essential to becoming a robust cyber power, which is the focus of this chapter.

Analysis and Decision

2019 ◽  
pp. 161-186
Author(s):  
Jeffrey A. Friedman
Keyword(s):  
Foreign Policy ◽  
Probabilistic Reasoning ◽  
Large Body ◽  
Decision Makers ◽  
Risky Decision ◽  
High Stakes ◽  
Policy Choices ◽  
Foreign Policies ◽  
The U.S ◽  
Over Time

This chapter explains how decision makers can incorporate assessments of uncertainty into high-stakes foreign policy choices. It begins by describing a simple analytic tool called break-even analysis, with which leaders can use explicit probability assessments as a point of leverage for determining whether or not a risky decision is worthwhile. The chapter then explains how transparent probabilistic reasoning is especially important for assessing strategic progress. In some cases, it can actually be impossible to make rigorous judgments about the extent to which foreign policies are making acceptable progress without assessing subjective probabilities in detail. This argument departs from a large body of existing scholarship on learning in international politics that assumes leaders can use a straightforward logic of trial and error to determine how they should update their strategic perceptions over time. The chapter provides examples of these dynamics drawn from the U.S. occupation of Iraq.

scholarly journals Procedures for Condition Mapping Using 360° Images

2020 ◽  
Vol 9 (1) ◽  
pp. 34
Author(s):  
Luigi Barazzetti ◽  
Mattia Previtali ◽  
Marco Scaioni
Keyword(s):  
Data Collection ◽  
Data Acquisition ◽  
Virtual Environment ◽  
Temporal Data ◽  
Novel Approach ◽  
Multi Temporal ◽  
Immersive Visualization ◽  
Over Time

The identification of deterioration mechanisms and their monitoring over time is an essential phase for conservation. This work aimed at developing a novel approach for deterioration mapping and monitoring based on 360° images, which allows for simple and rapid data collection. The opportunity to capture the whole scene around a 360° camera reduces the number of images needed in a condition mapping project, resulting in a powerful solution to document small and narrow spaces. The paper will describe the implemented workflow for deterioration mapping based on 360° images, which highlights pathologies on surfaces and quantitatively measures their extension. Such a result will be available as standard outputs as well as an innovative virtual environment for immersive visualization. The case of multi-temporal data acquisition will be considered and discussed as well. Multiple 360° images acquired at different epochs from slightly different points are co-registered to obtain pixel-to-pixel correspondence, providing a solution to quantify and track deterioration effects.

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