Lectures related to Anonymity and Accountability

Discusses the ethical implications of NLP systems, focusing on biases, toxicity, and privacy concerns in language models.

Covers ethical considerations in NLP, focusing on bias, toxicity, and misinformation.

Explores the development of faster architectures for saliency prediction using deep networks and pruning methods.

Delves into the impact of bias in machine learning models and the importance of evaluating potential harm in developing such systems.

Discusses anonymity, dark side issues, mitigation strategies, and governance in online forums.

Addresses the significance of framing and narratives in AI ethics and their impact on technology development and societal perceptions.

Explores challenges in data assumptions, biases, and more in research, including incomplete write-ups and frustrations of newcomers.

Introduces the Critical Data Studies course, covering data models, trust, reproducibility, biases, and ethics.

Explores ethical challenges in NLP systems, including biases, toxicity, privacy, and disinformation.

Explores the ethical implications of deploying machine learning algorithms and emphasizes the importance of fairness in decision-making processes.

Delves into ethics and law in AI, focusing on values, normative ambitions, and ethical challenges.

Explores the ethical obligation to act for the greater good and ensure equal rights and benefits distribution.

Explores the ethical challenges of AI in finance, including biases, market manipulation, and the need for ethical AI models.

Covers empirical risk minimization, statistical learning, and examples of cancer prediction, house pricing, and image generation.

Explores the Ethics and Law of AI, focusing on data ethics, bias, and social justice in AI systems.

Explores the Ethics of AI, focusing on Corporate Digital Responsibility and the role of government in regulating AI initiatives.

Explores the impact of new technologies on recruitment, emphasizing the importance of fair and accurate tools.

Delves into the ethical impact of AI on labor, social interactions, and war, exploring framing and narratives.

Covers the marketing plan, implementation, and ethics, using the Ford Pinto case as an example.

Explores the ethical aspects of AI, emphasizing autonomy, responsibility, and accountability in innovation processes.