Education for AI, not AI for Education: The Role of Education and Ethics in National AI Policy Strategies

Schiff, Daniel

doi:10.1007/s40593-021-00270-2

Cited by 92 publications

(72 citation statements)

References 83 publications

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“…While these measures are fundamental for guaranteeing an equitable access to the opportunities offered by AI, further funding could extend to other EC's policy recommendations such as the integration of ethics and humanities into AI and STEM curricula, the strengthening of the multidisciplinary research environment and the improvement of gender balance in computer science and engineering disciplines. These findings are aligned with those presented in Schiff (2021), who also provides recommendations to boost ethics and policy-oriented AI in education research and create a real impact for the public good.…”

Section: Discussionsupporting

confidence: 81%

Investing in AI for social good: an analysis of European national strategies

2022

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Artificial Intelligence (AI) has become a driving force in modern research, industry and public administration and the European Union (EU) is embracing this technology with a view to creating societal, as well as economic, value. This effort has been shared by EU Member States which were all encouraged to develop their own national AI strategies outlining policies and investment levels. This study focuses on how EU Member States are approaching the promise to develop and use AI for the good of society through the lens of their national AI strategies. In particular, we aim to investigate how European countries are investing in AI and to what extent the stated plans contribute to the good of people and society as a whole. Our contribution consists of three parts: (i) a conceptualization of AI for social good highlighting the role of AI policy, in particular, the one put forward by the European Commission (EC); (ii) a qualitative analysis of 15 European national strategies mapping investment plans and suggesting their relation to the social good (iii) a reflection on the current status of investments in socially good AI and possible steps to move forward. Our study suggests that while European national strategies incorporate money allocations in the sphere of AI for social good (e.g. education), there is a broader variety of underestimated actions (e.g. multidisciplinary approach in STEM curricula and dialogue among stakeholders) that can boost the European commitment to sustainable and responsible AI innovation.

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Section: Discussionsupporting

confidence: 81%

Investing in AI for social good: an analysis of European national strategies

2022

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“…13 AI can also help HLI design and implement student retention strategies that are less reactive and more proactive. This can help them immediately identify red flags and early warning signs in learners who are highly likely to fail academically (Schiff, 2021). This way, higher education institutions can develop student retention plans that anticipate student difficulties rather than react to student failures.…”

Section: Findings and Discussionmentioning

confidence: 99%

Impact of Artificial Intelligence On Higher Learning Institutions

Lainjo

Tsmouche

2023

IJETS

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Artificial intelligence applications in education have attracted the attention of multiple parties, including scholars, educators, governments, and researchers. The article aims to conduct a comprehensive and inclusive review of the proliferation and impact of Artificial intelligence on Higher Learning. Chronologically, the focus has been artificial intelligence applications in higher learning since the early 1950s. There needs to be more literature regarding the adoption of AI in higher education, resulting in a substantial limitation of this article. This article also discusses the role of cyber security in adopting AI in higher education. The authors have also discussed various applications of AI in higher education and the challenges. This article presents some recommendations. More research is needed as the recommendations are based on a limited number of scholarly articles. A Georgia State University case study conducted in 2015 substantiates AI adoption's benefits in higher education.

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“…Data on learner states (motivation, emotional states, for example) has also been taken into account, which can be deduced from physiological sensors (facial expression, seat posture and perspiration, for example). EDM uses methods and tools from the broader field of data mining [8,19], and a subdomain of computer science and AI that has been used for purposes as diverse as credit card fraud detection, genetic sequence analysis in bioinformatics, or analysis of customer buying behavior [20].…”

Section: Educational Data Mining (Edm)mentioning

confidence: 99%

Artificial Intelligent in Education

et al. 2022

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The application of Artificial Intelligence or AI in education has been the subject of academic research for more than 30 years. The field examines learning wherever it occurs, in traditional classrooms or at workplaces so to support formal education and lifelong learning. It combines interdisciplinary AI and learning sciences (such as education, psychology, neuroscience, linguistics, sociology and anthropology) in order to facilitate the development of effective adaptive learning environments and various flexible, inclusive tools. Nowadays, there are several new challenges in the field of education technology in the era of smart phones, tablets, cloud computing, Big Data, etc., whose current research questions focus on concepts such as ICT-enabled personalized learning, mobile learning, educational games, collaborative learning on social media, MOOCs, augmented reality application in education and so on. Therefore, to meet these new challenges in education, several fields of research using AI have emerged over time to improve teaching and learning using digital technologies. Moreover, each field of research is distinguished by its own vision and methodologies. In this article, to the authors present a state of the art finding in the fields of research of Artificial Intelligence in Education or AIED, Educational Data Mining or EDM and Learning Analytics or LA. We discuss their historical elements, definition attempts, objectives, adopted methodologies, application examples and challenges.

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Education for AI, not AI for Education: The Role of Education and Ethics in National AI Policy Strategies

Cited by 92 publications

References 83 publications

Investing in AI for social good: an analysis of European national strategies

Investing in AI for social good: an analysis of European national strategies

Impact of Artificial Intelligence On Higher Learning Institutions

Artificial Intelligent in Education

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