per Email
Allgemein
Singapur
Technology can displace lawyers, warns Chief Justice as he urges profession to adapt to new reality
Im Besonderen. Hilfreich auch bei Urkundenunterdrückung durch Richter! § 274 StGB
1. How artificial intelligence can help us make judges less biased
Predicting which judges are likely to be biased could give them the opportunity to consider more carefully
2. Temperature and Decisions: Evidence from 207,000 Court Cases
Abstract
If decisions with lasting consequences are influenced by extraneous or transient factors then welfare can be damaged. We analyze the impact of outdoor temperature on high-stakes decisions (immigration adjudications) made by professional decision-makers (US immigration judges). In our preferred specification, which includes spatial, temporal and judge fixed effects, and controls for various potential confounders, a one standard deviation increase in case-day temperature reduces positive decisions by 8.56%. This is despite judgements being made indoors, ‘protected’ by climate-control. Results are consistent with established links from temperature to mood and risk appetite and have important implications for evaluating the welfare-burden of climate change.
3. Machine Learning and the Rule of Law
Daniel L. Chen
Predictive judicial analytics holds the promise of increasing the fair- ness of law. Much empirical work observes inconsistencies in judicial behavior. By predicting judicial decisions—with more or less accuracy depending on judicial attributes or case characteristics—machine learn- ing offers an approach to detecting when judges most likely to allow extralegal biases to influence their decision making. In particular, low predictive accuracy may identify cases of judicial “indifference,” where case characteristics (interacting with judicial attributes) do no strongly dis- pose a judge in favor of one or another outcome. In such cases, biases may hold greater sway, implicating the fairness of the legal system.
Und überhaupt
When computers take the lead: The automation of leadership
Universität Berlin und Fribourg
Abstract
The importance of technology in the workplace has been, and continues to be, on an upward trajectory. Technological progress allows more and more functions once performed by humans to be automated. Theoretical conceptualizations in human-computer interaction (HCI) covered the evolution of computers from ‘tools’ to ‘partners’ in interaction with humans at work. However, nowadays computers have also begun to take over leadership functions, guiding and commanding human workers. We argue that conceptual coverage is in danger of falling short of this development and the implied profound change in hierarchy.
To close this gap, we propose the paradigm of ‘computers as leaders’ and call for a scientific discourse of computers performing leadership functions. Building on research in HCI and human-human leadership, we suggest a definition of computer-human leadership and a respective structural model, entangling interaction roles of the different human and computer agents involved. Moreover, we discuss criteria for evaluating automated leadership systems and questions of function allocation, before we bring our propositions together in a theoretical model depicting how humans come to accept and follow a computer leader. Finally, we discuss implications of the proposed paradigm and call for awareness of ethical issues.
Allgemein
Singapur
Technology can displace lawyers, warns Chief Justice as he urges profession to adapt to new reality
Im Besonderen. Hilfreich auch bei Urkundenunterdrückung durch Richter! § 274 StGB
1. How artificial intelligence can help us make judges less biased
Predicting which judges are likely to be biased could give them the opportunity to consider more carefully
2. Temperature and Decisions: Evidence from 207,000 Court Cases
Abstract
If decisions with lasting consequences are influenced by extraneous or transient factors then welfare can be damaged. We analyze the impact of outdoor temperature on high-stakes decisions (immigration adjudications) made by professional decision-makers (US immigration judges). In our preferred specification, which includes spatial, temporal and judge fixed effects, and controls for various potential confounders, a one standard deviation increase in case-day temperature reduces positive decisions by 8.56%. This is despite judgements being made indoors, ‘protected’ by climate-control. Results are consistent with established links from temperature to mood and risk appetite and have important implications for evaluating the welfare-burden of climate change.
3. Machine Learning and the Rule of Law
Daniel L. Chen
Predictive judicial analytics holds the promise of increasing the fair- ness of law. Much empirical work observes inconsistencies in judicial behavior. By predicting judicial decisions—with more or less accuracy depending on judicial attributes or case characteristics—machine learn- ing offers an approach to detecting when judges most likely to allow extralegal biases to influence their decision making. In particular, low predictive accuracy may identify cases of judicial “indifference,” where case characteristics (interacting with judicial attributes) do no strongly dis- pose a judge in favor of one or another outcome. In such cases, biases may hold greater sway, implicating the fairness of the legal system.
Und überhaupt
When computers take the lead: The automation of leadership
Universität Berlin und Fribourg
Abstract
The importance of technology in the workplace has been, and continues to be, on an upward trajectory. Technological progress allows more and more functions once performed by humans to be automated. Theoretical conceptualizations in human-computer interaction (HCI) covered the evolution of computers from ‘tools’ to ‘partners’ in interaction with humans at work. However, nowadays computers have also begun to take over leadership functions, guiding and commanding human workers. We argue that conceptual coverage is in danger of falling short of this development and the implied profound change in hierarchy.
To close this gap, we propose the paradigm of ‘computers as leaders’ and call for a scientific discourse of computers performing leadership functions. Building on research in HCI and human-human leadership, we suggest a definition of computer-human leadership and a respective structural model, entangling interaction roles of the different human and computer agents involved. Moreover, we discuss criteria for evaluating automated leadership systems and questions of function allocation, before we bring our propositions together in a theoretical model depicting how humans come to accept and follow a computer leader. Finally, we discuss implications of the proposed paradigm and call for awareness of ethical issues.
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