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Found 21 papers, 3 papers with code
Artificial Intelligence can facilitate selfish decisions by altering the appearance of interaction partners
The increasing prevalence of image-altering filters on social media and video conferencing technologies has raised concerns about the ethical and psychological implications of using Artificial Intelligence (AI) to manipulate our perception of others.
Lie detection algorithms attract few users but vastly increase accusation rates
We find that the few people (33\%) who elect to use the algorithm drastically increase their accusation rates (from 25\% in the baseline condition up to 86% when the algorithm flags a statement as a lie).
Classes of Aggregation Rules for Ethical Decision Making in Automated Systems
These results are a contribution for an AI designer that wants to justify the decisions made by an autonomous system.\\ \textit{Keywords:} Aggregation Operators; Permutation Process; Decision Analysis.
When Is It Acceptable to Break the Rules? Knowledge Representation of Moral Judgement Based on Empirical Data
We can invent novel rules on the fly.
Artificial Intelligence as an Anti-Corruption Tool (AI-ACT) -- Potentials and Pitfalls for Top-down and Bottom-up Approaches
Corruption continues to be one of the biggest societal challenges of our time.
SensitiveLoss: Improving Accuracy and Fairness of Face Representations with Discrimination-Aware Deep Learning
We propose a discrimination-aware learning method to improve both accuracy and fairness of biased face recognition algorithms.
Algorithmic Discrimination: Formulation and Exploration in Deep Learning-based Face Biometrics
We experimentally show that demographic groups highly represented in popular face databases have led to popular pre-trained deep face models presenting strong algorithmic discrimination.
Human detection of machine manipulated media
Here we report on a randomized experiment designed to study the effect of exposure to media manipulations on over 15, 000 individuals' ability to discern machine-manipulated media.
Evaluating Style Transfer for Text
Research in the area of style transfer for text is currently bottlenecked by a lack of standard evaluation practices.
Closing the AI Knowledge Gap
AI researchers employ not only the scientific method, but also methodology from mathematics and engineering.
Blaming humans in autonomous vehicle accidents: Shared responsibility across levels of automation
However, when both drivers make errors in cases of shared control between a human and a machine, the blame and responsibility attributed to the machine is reduced.
MemeSequencer: Sparse Matching for Embedding Image Macros
The analysis of the creation, mutation, and propagation of social media content on the Internet is an essential problem in computational social science, affecting areas ranging from marketing to political mobilization.
A Computational Model of Commonsense Moral Decision Making
We introduce a new computational model of moral decision making, drawing on a recent theory of commonsense moral learning via social dynamics.
A Voting-Based System for Ethical Decision Making
We present a general approach to automating ethical decisions, drawing on machine learning and computational social choice.
Regulating Highly Automated Robot Ecologies: Insights from Three User Studies
As in the study of political systems in which governments regulate human societies, our studies analyze how interactions between HARE and regulators are impacted by regulatory power and individual (robot or agent) autonomy.
Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm
NLP tasks are often limited by scarcity of manually annotated data.
Ranked #1 on
Transfer Learning
on Amazon Review Polarity
Cooperating with Machines
Here, we combine a state-of-the-art machine-learning algorithm with novel mechanisms for generating and acting on signals to produce a new learning algorithm that cooperates with people and other machines at levels that rival human cooperation in a variety of two-player repeated stochastic games.
Superintelligence cannot be contained: Lessons from Computability Theory
Superintelligence is a hypothetical agent that possesses intelligence far surpassing that of the brightest and most gifted human minds.
Experimental Assessment of Aggregation Principles in Argumentation-enabled Collective Intelligence
On the Web, there is always a need to aggregate opinions from the crowd (as in posts, social networks, forums, etc.).
Pareto Optimality and Strategy Proofness in Group Argument Evaluation (Extended Version)
An inconsistent knowledge base can be abstracted as a set of arguments and a defeat relation among them.
Judgment Aggregation in Multi-Agent Argumentation
After characterising the sufficient and necessary conditions for satisfying collective rationality, we study whether restricting the domain of argument-wise plurality voting to classical semantics allows us to escape the impossibility result.
