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pro vyhledávání: '"Krafft, P. M."'
Autor:
Hawkins, Robert D., Berdahl, Andrew M., Pentland, Alex "Sandy", Tenenbaum, Joshua B., Goodman, Noah D., Krafft, P. M.
Groups coordinate more effectively when individuals are able to learn from others' successes. But acquiring such knowledge is not always easy, especially in real-world environments where success is hidden from public view. We suggest that social infe
Externí odkaz:
http://arxiv.org/abs/2212.00869
Large-scale social networks are thought to contribute to polarization by amplifying people's biases. However, the complexity of these technologies makes it difficult to identify the mechanisms responsible and to evaluate mitigation strategies. Here w
Externí odkaz:
http://arxiv.org/abs/2208.07261
How do we design and deploy crowdsourced prediction platforms for real-world applications where risk is an important dimension of prediction performance? To answer this question, we conducted a large online Wisdom of the Crowd study where participant
Externí odkaz:
http://arxiv.org/abs/2007.09505
Recent concern about harms of information technologies motivate consideration of regulatory action to forestall or constrain certain developments in the field of artificial intelligence (AI). However, definitional ambiguity hampers the possibility of
Externí odkaz:
http://arxiv.org/abs/1912.11095
Autor:
Katell, Michael, Young, Meg, Herman, Bernease, Dailey, Dharma, Tam, Aaron, Guetler, Vivian, Binz, Corinne, Raz, Daniella, Krafft, P. M.
A wave of recent scholarship documenting the discriminatory harms of algorithmic systems has spurred widespread interest in algorithmic accountability and regulation. Yet effective accountability and regulation is stymied by a persistent lack of reso
Externí odkaz:
http://arxiv.org/abs/1912.02943
Akademický článek
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Autor:
Almaatouq, Abdullah, Noriega-Campero, Alejandro, Alotaibi, Abdulrahman, Krafft, P. M., Moussaid, Mehdi, Pentland, Alex
Publikováno v:
Proceedings of the National Academy of Sciences, 117(21), 11379-11386 (2020)
Social networks continuously change as new ties are created and existing ones fade. It is widely noted that our social embedding exerts a strong influence on what information we receive and how we form beliefs and make decisions. However, most empiri
Externí odkaz:
http://arxiv.org/abs/1805.04766
Flocking is a coordinated collective behavior that results from local sensing between individual agents that have a tendency to orient towards each other. Flocking is common among animal groups and might also be useful in robotic swarms. In the inter
Externí odkaz:
http://arxiv.org/abs/1804.08667
Publikováno v:
Peter Krafft, Nicol\'as Della Penna, Alex Pentland. (2018). An Experimental Study of Cryptocurrency Market Dynamics. ACM CHI Conference on Human Factors in Computing Systems (CHI)
As cryptocurrencies gain popularity and credibility, marketplaces for cryptocurrencies are growing in importance. Understanding the dynamics of these markets can help to assess how viable the cryptocurrnency ecosystem is and how design choices affect
Externí odkaz:
http://arxiv.org/abs/1801.05831
We study a distributed learning process observed in human groups and other social animals. This learning process appears in settings in which each individual in a group is trying to decide over time, in a distributed manner, which option to select am
Externí odkaz:
http://arxiv.org/abs/1705.03414