Alex Pentland

Alex Pentland
Massachusetts Institute of Technology | MIT · MIT Media Laboratory

About

279
Publications
86,154
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25,657
Citations

Publications

Publications (279)
Preprint
Full-text available
Urban density, in the form of residents' and visitors' concentration, is long considered to foster diverse exchanges of interpersonal knowledge and skills, which are intrinsic to sustainable human settlements. However, with current urban studies primarily devoted to city and district-level analysis, we cannot unveil the elemental connection between...
Article
Full-text available
Numerous studies over the past decades established that real-world networks typically follow preferential attachment and detachment principles. Subsequently, this implies that degree fluctuations monotonically increase while rising up the ‘degree ladder’, causing high-degree nodes to be prone for attachment of new edges and for detachment of existi...
Preprint
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Diversity of physical encounters and social interactions in urban environments are known to spur economic productivity and innovation in cities, while also to foster social capital and resilience of communities. However, mobility restrictions during the pandemic have forced people to substantially reduce urban physical encounters, raising questions...
Preprint
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We introduce $\pi$-test, a privacy-preserving algorithm for testing statistical independence between data distributed across multiple parties. Our algorithm relies on privately estimating the distance correlation between datasets, a quantitative measure of independence introduced in Sz\'ekely et al. [2007]. We establish both additive and multiplica...
Article
Many studies propose methods for finding the best location for new stores and facilities, but few studies address the store closing problem. As a result of the recent COVID-19 pandemic, many companies have been facing financial issues. In this situation, one of the most common solutions to prevent loss is to downsize by closing one or more chain st...
Article
User profiling refers to inferring people’s attributes of interest ( AoIs ) like gender and occupation, which enables various applications ranging from personalized services to collective analyses. Massive nonlinguistic audio data brings a novel opportunity for user profiling due to the prevalence of studying spontaneous face-to-face communication....
Chapter
Machines powered by artificial intelligence increasingly mediate our social, cultural, economic, and political interactions. This chapter frames and surveys the emerging interdisciplinary field of machine behaviour: the scientific study of behaviour exhibited by intelligent machines. It outlines the key research themes, questions, and landmark rese...
Preprint
Full-text available
How does the visual design of digital platforms impact user behavior and the resulting environment? A body of work suggests that introducing social signals to content can increase both the inequality and unpredictability of its success, but has only been shown in the context of music listening. To further examine the effect of social influence on m...
Article
Researchers across cognitive science, economics, and evolutionary biology have studied the ubiquitous phenomenon of social learning—the use of information about other people's decisions to make your own. Decision-making with the benefit of the accumulated knowledge of a community can result in superior decisions compared to what people can achieve...
Article
Full-text available
The COVID-19 pandemic is causing mass disruption to our daily lives. We integrate mobility data from mobile devices and area-level data to study the walking patterns of 1.62 million anonymous users in 10 metropolitan areas in the United States. The data covers the period from mid-February 2020 (pre-lockdown) to late June 2020 (easing of lockdown re...
Article
Customer patronage behavior has been widely studied in market share modeling contexts, which is an essential step toward estimating retail sales and finding new store locations in a competitive setting. Existing studies have conducted surveys to estimate merchants' market share and factors of attractiveness to use in various proposed mathematical m...
Preprint
Full-text available
The COVID-19 pandemic has caused mass disruption to our daily lives. Mobility restrictions implemented to reduce the spread of COVID-19 have impacted walking behavior, but the magnitude and spatio-temporal aspects of these changes have yet to be explored. Walking is the most common form of physical activity and non-motorized transport, and so has a...
Article
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Abstract Much recent work has illuminated the growth, innovation, and prosperity of entire cities, but there is relatively less evidence concerning the growth and prosperity of individual neighborhoods. In this paper we show that diversity of amenities within a city neighborhood, computed from openly available points of interest on digital maps, ac...
Preprint
Compositional and relational learning is a hallmark of human intelligence, but one which presents challenges for neural models. One difficulty in the development of such models is the lack of benchmarks with clear compositional and relational task structure on which to systematically evaluate them. In this paper, we introduce an environment called...
Article
Full-text available
The idea that many businesses rely heavily on data to produce or market goods and services is not new. Indeed, even in 2018, four of the six top companies in market valuation — Amazon, Alphabet, Facebook, and Alibaba — based their business models on the use of data to optimize advertising. However, data differs greatly from traditional factors of p...
Preprint
Cryptocurrencies and Blockchain-based technologies are disrupting all markets. While the potential of such technologies remains to be seen, there is a current need to understand emergent patterns of user behavior and token adoption in order to design future products. In this paper we analyze the social dynamics taking place during one arbitrary day...
Chapter
Full-text available
That data helps to generate value is a very robust idea: We talk about data as “the new oil”, and the concept of “big data” is widely spread. While this idea applies to many areas of modern life, it is especially prominent in the financial sector, where data-based insights are crucial to make the right decisions and adequately navigate through the...
Preprint
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Governments and researchers around the world are implementing digital contact tracing solutions to stem the spread of infectious disease, namely COVID-19. Many of these solutions threaten individual rights and privacy. Our goal is to break past the false dichotomy of effective versus privacy-preserving contact tracing. We offer an alternative appro...
Article
Full-text available
How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning...
Article
Full-text available
Global financial crises have led to the understanding that classical econometric models are limited in comprehending financial markets in extreme conditions, partially since they disregarded complex interactions within the system. Consequently, in recent years research efforts have been directed towards modeling the structure and dynamics of the un...
Preprint
Full-text available
Much recent work has illuminated the growth, innovation, and prosperity of entire cities, but there is relatively less evidence concerning the growth and prosperity of individual neighborhoods. In this paper we show that diversity of amenities within a city neighborhood, computed from openly available points of interest on digital maps, accurately...
Article
This paper analyzes millions of credit card transaction records during several months for tens of thousands of individuals from two different countries. The study shows that, purchase patterns are strongly correlated with important societal indices such as socioeconomic status and political inclination. The results suggest the possibility of unders...
Article
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Bees play a key role in pollination of crops and in diverse ecosystems. There have been multiple reports in recent years illustrating bee population declines worldwide. The search for more accurate forecast models can aid both in the understanding of the regular behavior and the adverse situations that may occur with the bees. It also may lead to b...
Preprint
Discriminating between causality and correlation is a major problem in machine learning, and theoretical tools for determining causality are still being developed. However, people commonly make causality judgments and are often correct, even in unfamiliar domains. What are humans doing to make these judgments? This paper examines differences in hum...
Article
Full-text available
Social behaviours emerge from the exchange of information among individuals-constrained by and reciprocally influencing the structure of information flows. The Internet radically transformed communication by democratizing broadcast capabilities and enabling easy and borderless formation of new acquaintances. However, actual information flows are he...
Preprint
Does receiving a gift encourage the recipient to send more gifts? Causal identification of behavioral contagion is very challenging, especially based on observational data from social networks. Given that the online monetary gift (also known as a "red packet") in WeChat groups is randomly split between group members, we are able to conduct a natura...
Conference Paper
Full-text available
Thompson Sampling provides an efficient technique to introduce prior knowledge in the multi-armed bandit problem, along with providing remarkable empirical performance. In this paper, we revisit the Thompson Sampling algorithm under rewards drawn from symmetric alpha-stable distributions, which are a class of heavy-tailed probability distributions...
Preprint
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In Turkey the increasing tension, due to the presence of 3.4 million Syrian refugees, demands the formulation of effective integration policies. Moreover, their design requires tools aimed at understanding the integration of refugees despite the complexity of this phenomenon. In this work, we propose a set of metrics aimed at providing insights and...
Article
Full-text available
Autonomous Vehicles (AVs), drones and robots will revolutionize our way of travelling and understanding urban space. In order to operate, all of these devices are expected to collect and analyze a lot of sensitive data about our daily activities. However, current operational models for these devices have extensively relied on centralized models of...
Chapter
Autonomous Vehicles (AVs), drones and robots will revolutionize our way of travelling and understanding urban space. In order to operate, all of these devices are expected to collect and analyze a lot of sensitive data about our daily activities. However, current operational models for these devices have extensively relied on centralized models of...
Preprint
Full-text available
Swarm robotics systems are envisioned to become an important component of both academic research and real-world applications. However, in order to reach widespread adoption, new models that ensure the secure cooperation of these systems need to be developed. This work proposes a novel model to encapsulate cooperative robotic missions in Merkle tree...
Article
Full-text available
Machines powered by artificial intelligence increasingly mediate our social, cultural, economic and political interactions. Understanding the behaviour of artificial intelligence systems is essential to our ability to control their actions, reap their benefits and minimize their harms. Here we argue that this necessitates a broad scientific researc...
Conference Paper
Full-text available
Modern cities are growing ecosystems that face new challenges due to the increasing population demands. One of the many problems they face nowadays is waste management, which has become a pressing issue requiring new solutions. Swarm robotics systems have been attracting an increasing amount of attention in the past years and they are expected to b...
Preprint
Full-text available
Customer patronage behavior has been widely studied in market share modeling contexts, which is an essential step towards modeling and solving competitive facility location problems. Existing studies have conducted surveys to estimate merchants' market share and factors of attractiveness to use in various proposed mathematical models. Recent trends...
Preprint
Full-text available
The analysis of credit card transactions allows gaining new insights into the spending occurrences and mobility behavior of large numbers of individuals at an unprecedented scale. However, unfolding such spatiotemporal patterns at a community level implies a non-trivial system modeling and parametrization, as well as, a proper representation of the...
Conference Paper
Society increasingly relies on machine learning models for automated decision making. Yet, efficiency gains from automation have come paired with concern for algorithmic discrimination that can systematize inequality. Recent work has proposed optimal post-processing methods that randomize classification decisions for a fraction of individuals, in o...
Article
Full-text available
In this article, the authors discuss and analyze their approach to the Fragile Families Challenge. The data consisted of more than 12,000 features (covariates) about the children and their parents, schools, and overall environments from birth to age 9. The authors’ modular and collaborative approach parallelized prediction tasks and relied primaril...
Article
2019 International Joint Conferences on Artificial Intelligence. All rights reserved. Thompson Sampling provides an efficient technique to introduce prior knowledge in the multiarmed bandit problem, along with providing remarkable empirical performance. In this paper, we revisit the Thompson Sampling algorithm under rewards drawn from symmetric α-s...
Article
2019 Copyright held by the owner/author(s). Society increasingly relies on machine learning models for automated decision making. Yet, efficiency gains from automation have come paired with concern for algorithmic discrimination that can systematize inequality. Recent work has proposed optimal post-processing methods that randomize classification d...
Article
Full-text available
The breadcrumbs we leave behind when using our mobile phones—who somebody calls, for how long, and from where—contain unprecedented insights about us and our societies. Researchers have compared the recent availability of large-scale behavioral datasets, such as the ones generated by mobile phones, to the invention of the microscope, giving rise to...
Article
Full-text available
Social interactions among humans create complex networks and – despite a recent increase of online communication – the interactions mediated through physical proximity remain a fundamental way for people to connect. A common way to quantify the nature of the links between individuals is to consider repeated interactions: frequently occurring intera...
Article
Full-text available
Societal unrest and similar events are important for societies, but it is often difficult to quantify their effects on individuals, hindering a timely and effective policy-making in emergencies and in particular localized social shocks such as protests. Traditionally, effects are assessed through economic indicators or surveys with relatively low t...
Article
Full-text available
Abstract Customer retention is crucial in a variety of businesses as acquiring new customers is often more costly than keeping the current ones. As a consequence, churn prediction has attracted great attention from both the business and academic worlds. Traditional efforts in the financial domain mainly focus on domain specific variables such as pr...
Preprint
In this empirical paper, we investigate how learning agents can be arranged in more efficient communication topologies for improved learning. This is an important problem because a common technique to improve speed and robustness of learning in deep reinforcement learning and many other machine learning algorithms is to run multiple learning agents...
Article
Full-text available
Understanding the mechanisms of network formation is central in social network analysis. Network formation has been studied in many research fields with their different focuses; for example, network embedding algorithms in machine learning literature consider broad heterogeneity among agents while the social sciences emphasize the interpretability...
Article
Participants in cryptocurrency markets are in constant communication with each other about the latest coins and news releases. Do these conversations build hype through the contagiousness of excitement, help the community process information, or play some other role? Using a novel dataset from a major cryptocurrency forum, we conduct an exploratory...
Preprint
Full-text available
Modern cities are growing ecosystems that face new challenges due to the increasing population demands. One of the many problems they face nowadays is waste management, which has become a pressing issue requiring new solutions. Swarm robotics systems have been attracting an increasing amount of attention in the past years and they are expected to b...
Preprint
Full-text available
The Ethereum blockchain network is a decentralized platform enabling smart contract execution and transactions of Ether (ETH) [1], its designated cryptocurrency. Ethereum is the second most popular cryptocurrency with a market cap of more than 100 billion USD, with hundreds of thousands of transactions executed daily by hundreds of thousands of uni...
Chapter
Phenomena such as “small-world” and “six degrees of separation” reveal the connectivity between individuals that are seemingly unrelated in the society. Beyond merely connectivity, it has been shown in recent years that social contagion exists in online interactions. Along this line of investigation, we are interested in the subtle and invisible so...
Preprint
Centrality is a fundamental building block in network analysis. Existing centrality measures focus on the network topology without considering nodal characteristics. However, this ignorance is perilous if the cascade payoff does not grow monotonically with the size of the cascade. In this paper, we propose a new centrality measure, Cascade Centrali...
Article
The social phenomenon of familiar strangers was identified by Stanley Milgram in 1972 with a small-scale experiment. However, there has been limited research focusing on uncovering the phenomenon at a societal scale and simultaneously investigating the social relationships between familiar strangers. With the help of the large-scale mobile phone re...
Article
Full-text available
To understand and manage complex organizations, we must develop tools that are capable of measuring human social interaction accurately and uniformly. Current technologies that measure face to face communication do not measure interaction in a unified manner, often ignoring remote interaction which is an increasingly common communication modality....
Chapter
Full-text available
Mobile phone metadata is increasingly used for humanitar- ian purposes in developing countries as traditional data is scarce. Ba- sic demographic information is however often absent from mobile phone datasets, limiting the operational impact of the datasets. For these rea- sons, there has been a growing interest in predicting demographic infor- mat...
Article
Targeted vaccination, whether to minimize the forward transmission of infectious diseases or their clinical impact, is one of the 'holy grails' of modern infectious disease outbreak response, yet it is difficult to achieve in practice due to the challenge of identifying optimal targets in real time. If interruption of disease transmission is the go...
Article
In this study, we build on previous research to understand the conditions within which the Wisdom of the Crowd (WoC) improves or worsens as a result of showing individuals the predictions of their peers. Our main novel contributions are: 1) a dataset of unprecedented size and detail; 2) we observe the novel effect of the importance of the unimodali...
Article
Being able to correctly aggregate the beliefs of many people into a single belief is a problem fundamental to many important social, economic and political processes such as policy making, market pricing and voting. Although there exist many models and mechanisms for aggregation, there is a lack of methods and literature regarding the aggregation o...
Article
The understanding and modeling of human purchase behavior in city environment can have important implications in the study of urban economy and in the design and organization of cities. In this article, we study human purchase behavior at the community level and argue that people who live in different communities but work at close-by locations coul...
Article
We draw upon a previously largely untapped literature on human collective intelligence as a source of inspiration for improving deep learning. Implicit in many algorithms that attempt to solve Deep Reinforcement Learning (DRL) tasks is the network of processors along which parameter values are shared. So far, existing approaches have implicitly uti...