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The use of a generative AI tool to create or even rewrite your assignments and then submitting that work as your own is akin to someone else doing your work for you.(1) A major aim of university education is learning how to digest information, consider that information carefully, and finally, combining that information with your own perspective through writing or discussion. This takes practice and is not only a skill employers are looking for, but is also an incredibly important life skill. Relying on generative AI to produce content that you haven’t created or engaged with meaningfully yourself, results in work that isn't truly your own and fails to reflect your personal development. If you do use generative AI, it’s essential to disclose which tools you used and how you employed them. For more information on this topic:
Generative AI tools can produce biased content for several reasons.(1) Everyone has biases based on their own personal experiences and the people who create AI tools can unintentionally embed those biases into the tools they create. Datasets can also can also contain biases, and if they are used to train an AI tool, it will have those inherent biases built in. It is also possible that the AI tool itself can inadvertently develop biases based off of the data used to train the tool.
So, if the people, the data, and the tools are biased, why are we using them? This is just to make you aware of the possibility of bias in AI. Bias exists everywhere and is something we all live with every day. Simply knowing it exists will better equip you to think critically about, for example, a generative AI's response to a prompt you provide.
For further study:
Creating, training, and deploying generative AI models demands substantial energy and generates carbon emissions. Additionally, these processes use a considerable amount of water for cooling purposes.(1) While researchers and companies are investigating ways to enhance the sustainability of generative AI, it remains crucial to weigh the environmental impact of your AI usage and strive to use these tools as efficiently as possible. For more information on this issue, the following is a short, curated list of articles on this topic:
When any new technology is introduced that can infringe on rights management and copyright, regulatory efforts require time to adapt and address these developments. A good example of this is writers whose content has been used to train AI.
By submitting content that you've created to AI platforms via prompts or uploads, you may inadvertently grant the AI tool the right to reuse and distribute this content, which could lead to copyright or privacy issues.(1) Exercise caution when providing content, particularly information or data that you did not create, to AI platforms. For further information, please read the University of Toronto's Generative AI Tools Copyright & Considerations FAQ.
Artificial Intelligence and Sustainability by
This book gives readers the tools to craft AI systems that don't just thrive today, but endure sustainably into the future. Whether a trailblazer or an aspiring innovator, this book enables readers to resonate with the ambitions of software developers, data scientists, and AI practitioners. The author covers the latest techniques and best practices for energy efficiency, reducing carbon footprints, and ensuring fair and ethical AI. The book also addresses important issues such as AI governance, managing risks, and ensuring transparency. Topics covered include understanding the relationship between AI and sustainable development, strategies for building efficient AI systems, and ethical considerations in AI development, among others. The author includes case studies of companies and organizations that have successfully implemented sustainable AI software development practices. Therefore, this book will be of interest to AI practitioners, academics, researchers, and lecturers in computer science, artificial intelligence, machine learning and data sciences.
Ethics and Artificial Intelligence by
It is a book made up of questions, some without certain answers, that attempts to open the reader's mind to new and, perhaps, futuristic scenarios. There are two diametrically opposed approaches to artificial intelligence today. On the one hand, there are the techno-pessimists who see only dystopian scenarios and experience technological progress with apprehension, emphasising the dangers, and on the other hand, there are the techno-optimists who, on the other hand, tend to overestimate the positive effects, going so far as to attribute almost thaumaturgic virtues to technological progress. Our approach is meant to be secular and scientific; the risks must not be concealed, nor must they be overestimated, just as the positive aspects must not be emphasised. And, in any case, as in any social phenomenon, the governance of processes and the definition of a system of rules and policies are the aspects that can create advantages or disadvantages and, above all, can determine who are the beneficiaries of the advantages and who have to bear the disadvantages. Like any new technology, this too can be dehumanising, but technology is a tool that depends on how it is used and by whom it is used. that of ethics is, therefore, a fundamental aspect. Therefore, one should neither be a techno-optimist nor a techno-pessimist, but should be aware that governing the economic and social structural changes that the advent of artificial intelligence will cause will be crucial to ensure prosperity for future generations and to avoid negative and even apocalyptic scenarios. So no futurist dystopias! Humanity has so far always been able to govern technological progress, it certainly has the potential to govern what some have called 'the Final Invention', but it will only succeed if it is able to understand the peculiarities of this new process of technological development and give it ethical content.The book provides a thoughtful review of the relationship between artificial intelligenceand ethics, approaching the issue from different perspectives: philosophical, technological, economic and legal. This will be one of the most important issues that Humanity will have to face and resolve.
The Frontlines of Artificial Intelligence Ethics by
This foundational text examines the intersection of AI, psychology, and ethics, laying the groundwork for the importance of ethical considerations in the design and implementation of technologically supported education, decision support, and leadership training. AI already affects our lives profoundly, in ways both mundane and sensational, obvious and opaque. Much academic and industrial effort has considered the implications of this AI revolution from technical and economic perspectives, but the more personal, humanistic impact of these changes has often been relegated to anecdotal evidence in service to a broader frame of reference. Offering a unique perspective on the emerging social relationships between people and AI agents and systems, Hampton and DeFalco present cutting-edge research from leading academics, professionals, and policy standards advocates on the psychological impact of the AI revolution. Structured into three parts, the book explores the history of data science, technology in education, and combatting machine learning bias, as well as future directions for the emerging field, bringing the research into the active consideration of those in positions of authority. Exploring how AI can support expert, creative, and ethical decision making in both people and virtual human agents, this is essential reading for students, researchers, and professionals in AI, psychology, ethics, engineering education, and leadership, particularly military leadership.
Responsible Artificial Intelligence by
In this book, the author examines the ethical implications of Artificial Intelligence systems as they integrate and replace traditional social structures in new sociocognitive-technological environments. She discusses issues related to the integrity of researchers, technologists, and manufacturers as they design, construct, use, and manage artificially intelligent systems; formalisms for reasoning about moral decisions as part of the behavior of artificial autonomous systems such as agents and robots; and design methodologies for social agents based on societal, moral, and legal values. Throughout the book the author discusses related work, conscious of both classical, philosophical treatments of ethical issues and the implications in modern, algorithmic systems, and she combines regular references and footnotes with suggestions for further reading. This short overview is suitable for undergraduate students, in both technical and non-technical courses, andfor interested and concerned researchers, practitioners, and citizens.
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