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The IEEE TechEthics resources library provides access to an extensive set of content covering a wide range of technology topics.

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Gender and Technology: The Case of the Energy Sector

Energy policy is often formulated in a gender-neutral manner; that is, it is assumed by policy makers that women and men use and benefit equally from current energy systems. However, policies are incorrectly considered neutral by policy makers since they ignore the differential impacts they have on different genders and socioeconomic and cultural groups. Based on such false assumptions, the policies are less effective and/or have unintended effects. This white paper by the IEEE Dignity, Inclusion, Identity, Trust, and Agency (DIITA) Industry Connections Program discusses these issues.

Framing Cognitive Machines: A Sociotechnical Taxonomy

This paper proposes a taxonomy for the analysis of socio-economic disruptions caused by technological innovations. A transdisciplinary principled approach is used to build the taxonomy through categorization and characterization of technologies using concepts and definitions originating from cybernetics, occupational science, and economics. Concrete illustrations of concepts and uses are offered, including an Industry 5.0 case study as an application of the taxonomy.

Essential Skills for IT Professionals in the AI Era

Artificial Intelligence is transforming industries worldwide, creating new opportunities in health care, finance, customer service, and other disciplines. But the ascendance of AI raises concerns about job displacement, especially as the technology might automate tasks traditionally done by humans. This article presents some skills IT professionals need to stay relevant, including key insights into AI ethics.

Disdata: The Disaggregation of Disability Data

Building inclusive and accessible systems and technologies is of the highest importance if we are to create a fairer future. Part of the way we can improve this is by driving discussion and furthering understanding in the field of inclusive information technology. This fireside discussion at WEDF addresses the ‘disaggregation of disability related data’, and how leveraging this can make a meaningful difference – potentially meeting the needs of all.

Evolving Landscape of Responsible AI

With the recent strides in Generative AI to create new content, ChatGPT has taken the world by storm. Yet there are daily reports of AI harm. Over 90 percent of businesses using AI say Trustworthy and explainable AI is critical to business. More than half of companies cite significant barriers to getting there including a lack of skills, inflexible governance tools, biased data, and more. Responsible AI is an evolving landscape that requires a comprehensive approach around people, processes, systems, data, and algorithms. This panel discussion explores this ever-changing and complex landscape from the perspective of principles, tools and frameworks, legislatures, and standards.

Enhancing the Fairness and Performance of Edge Cameras with Explainable AI

The rising use of Artificial Intelligence (AI) in human detection on Edge camera systems has led to accurate but complex models, challenging to interpret and debug. The research described in this paper presents a diagnostic method using XAI for model debugging, with expert-driven problem identification and solution creation. The approach helps identify model biases, essential for achieving fair and trustworthy models.

Custom Developer GPT for Ethical AI Solutions

This paper provides motivation for the need of a new software artefact: a custom Generative Pre-trained Transformer (GPT) for developers to discuss and solve ethical issues through AI engineering. The use of such a tool can allow practitioners to engineer AI solutions which meet legal requirements and satisfy diverse ethical perspectives. The paper details the idea and demonstrates a use case.

Do Generative AI Tools Ensure Green Code? An Investigative Study

The sustainability or ’greenness’ of software is typically determined by the adoption of sustainable coding practices. Despite their potential advantages, there is a significant lack of studies on the sustainability aspects of AI-generated code. Specifically, how environmentally friendly is the AI-generated code based upon its adoption of sustainable coding practices? This paper presents the results of an early investigation into the sustainability aspects of AI-generated code across three popular generative AI tools — ChatGPT, BARD, and Copilot.

Ethics in Leadership: Creating an Ethical Culture at IEEE

Developed specifically for IEEE volunteers by the IEEE Ethics and Member Conduct Committee (EMCC), this session addresses why ethics is important for volunteers and IEEE, how IEEE defines and embraces an ethical culture, and key approaches to ethical leadership and culture.
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