Toward accountable human-centered AI: rationale and promising directions

Abstract

Purpose Along with the various beneficial uses of artificial intelligence (AI), there are various unsavory concomitants including the inscrutability of AI tools (and the opaqueness of their mechanisms), the fragility of AI models under adversarial settings, the vulnerability of AI models to bias throughout their pipeline, the high planetary cost of running large AI models and the emergence of exploitative surveillance capitalism-based economic logic built on AI technology. This study aims to document these harms of AI technology and study how these technologies and their developers and users can be made more accountable. Design/methodology/approach Due to the nature of the problem, a holistic, multi-pronged approach is required to understand and counter these potential harms. This paper identifies the rationale for urgently focusing on human-centered AI and provide an outlook of promising directions including technical proposals. Findings AI has the potential to benefit the entire society, but there remains an increased risk for vulnerable segments of society. This paper provides a general survey of the various approaches proposed in the literature to make AI technology more accountable. This paper reports that the development of ethical accountable AI design requires the confluence and collaboration of many fields (ethical, philosophical, legal, political and technical) and that lack of diversity is a problem plaguing the state of the art in AI. Originality/value This paper provides a timely synthesis of the various technosocial proposals in the literature spanning technical areas such as interpretable and explainable AI; algorithmic auditability; as well as policy-making challenges and efforts that can operationalize ethical AI and help in making AI accountable. This paper also identifies and shares promising future directions of research.

Engineering Education in the Era of ChatGPT: Promise and Pitfalls of Generative AI for Education

“…This is especially true for engineers, who rely on a wide range of tools and techniques to solve complex problems and design innovative solutions. As the tools available to engineers become more sophisticated 5 Prompt engineering with OpenAI API https://help.openai.com/en/articles/ 6654000-best-practices-for-prompt-engineering-with-openai-api 6 Rob Toews, The Biggest Opportunity In Generative AI Is Language, Not Images, https://www.forbes.com/sites/robtoews/2022/11/ 06/the-biggest-opportunity-in-generative-ai-is-language-not-images and readily accessible, it becomes increasingly important to be able to identify the right tool for the right task and to use it effectively. This requires resourcefulness, which involves using various strategies to locate and evaluate information and resources, as well as the ability to think holistically and consider the big picture [19], [24].…”

“…It is also important to think of ways we can ensure equitable access to such technology developed by AI research organizations and corporations [6]. Tufekci also makes the case that we should focus much more on equitability as the use of generative AI technology becomes more prevalent in education and society.…”

Developing smart city services using intent‐aware recommendation systems: A survey

“…226 IARS actively contribute to the smart city vision but we should be beware of potential pitfalls, risks, and challenges when we leverage technologies such as big data, machine learning, and artificial intelligence. 225,[227][228][229] Various data biases may cause detrimental recommendations in human-centric services, such as recommendation lists could be biased towards specific human groups, and genders. 225,230 Apart from data-oriented challenges, there are other risks to intelligent predictions in smart city services.…”

“…IARS can optimize smart city services development, but ethical issues such as ethical governance, careful policies, and mature institutions play a key role in their adoption 226 . IARS actively contribute to the smart city vision but we should be beware of potential pitfalls, risks, and challenges when we leverage technologies such as big data, machine learning, and artificial intelligence 225,227‐229 . Various data biases may cause detrimental recommendations in human‐centric services, such as recommendation lists could be biased towards specific human groups, and genders 225,230 …”

A Cross-Disciplinary Examination of the Instructional Uses of ChatGPT in Higher Education

“…Although ChatGPT's potential uses by students for generating essays and its risks for increasing plagiarism have received significant attention, its potential uses by instructors in higher education remain under-examined (Qadir, 2022;Qadir et al, 2022). As such, we explored capabilities of ChatGPT in generating course assessment tasks in two disciplinary contexts, industrial engineering (IE) and applied linguistics.…”