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The rapid advancement of generative AI (gen AI) has regulators around the world racing to understand, control, and guarantee the safety of the technology—all while preserving its potential benefits. Across industries, gen AI adoption has presented a new challenge for risk and compliance functions: how to balance use of this new technology amid an evolving—and uneven—regulatory framework.
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About the authors
As governments and regulators try to define what such a control environment should look like, the developing approaches are fragmented and often misaligned, making it difficult for organizations to navigate and causing substantial uncertainty.
In this article, we explain the risks of AI and gen AI and why the technology has drawn regulatory scrutiny. We also offer a strategic road map to help risk functions navigate the uneven and changing rule-making landscape—which is focused not only on gen AI but all artificial intelligence.
ChatGPT took the world by surprise last year, almost as if we had discovered another form of life. Since then, artificial intelligence (AI) has been evolving unchecked, to the point where some are even talking about a “technological Wild West”.
The opportunities presented by artificial intelligence are as daunting as its dangers.
But how should artificial intelligence be regulated? Who should do it? How can we ensure that the companies and individuals who develop and use AI respect ethical principles? Should we legislate now for a technology that we still understand so little about? Is it even possible to do? Does Bill C-27, tabled by the federal government, address these crucial issues? And what role should Quebec and the other provinces play?
These are just some of the questions posed by the series “How to legislate on artificial intelligence”, which presents five texts exploring these and other issues, taking stock of the current situation and suggesting avenues for consideration by governments, industry and the public debate in general.
The authors are seasoned experts, many of whom sit on global committees on AI, including ethicists Jocelyn Maclure and Alexis Morin-Martel, professors Céline Castets-Renard and Anne-Sophie Hulin, University of Ottawa vice-dean Jennifer Quaid, and constitutionalist and former minister Benoît Pelletier.
The advent of AI presents opportunities for progress in critical areas, along with unique challenges, for countries in the Global South.
ChatGPT, which stands for Chat Generative Pre-trained Transformer, is a text-generating AI chatbot developed by OpenAI and launched on November 30, 2022. This briefing examines the influence of ChatGPT usage on organizations and workers.
Which roles are most impacted by using ChatGPT and which are the least impacted? For which skill does generative AI have the largest organizational implications? Are there concerns about ChatGPT’s safety and security and, if so, how should they be addressed?
Read the issue briefing to get our full analysis.
Contents
Key findings
Introduction
ChatGPT has the largest implications for roles using writing and programming skills
STEM and knowledge workers are likely to be the most impacted
Organizational implications
Appendix A—Bibliography
When artificial intelligence went mainstream with the public release of ChatGPT in November 2022, it immediately sent ripples through the world of education. Concerns about equity in AI, data privacy, and how to teach ethical AI skills became heated topics at faculty meetings and in classrooms. Two things have become clear: This technology is already transforming education—and people have many questions.
Science Friday hosted a virtual conversation with experts in AI and education in October 2023 to understand the potential AI holds for education and some of the pitfalls to be confronted as it comes to schools across the country. While the path forward may be challenging and occasionally confusing, our guests suggest that by allowing students to lead and guiding them to use AI responsibly, education stands to benefit from innovative tools that will, no doubt, change our world. Here, we recap some of the ideas and insights that came out of that conversation.
People with disability face persisting difficulties in the labour market. There are concerns that AI, if managed poorly, could further exacerbate these challenges. Yet, AI also has the potential to create more inclusive and accommodating environments and might help remove some of the barriers faced by people with disability in the labour market. Building on interviews with more than 70 stakeholders, this report explores the potential of AI to foster employment for people with disability, accounting for both the transformative possibilities of AI-powered solutions and the risks attached to the increased use of AI for people with disability. It also identifies obstacles hindering the use of AI and discusses what governments could do to avoid the risks and seize the opportunities of using AI to support people with disability in the labour market.
AI promises efficiency gains, but they come at the cost of alienation, Benjamin Mitchell-Yellin writes. Generative artificial intelligence is all the rage—in both senses of the term. Many people in higher education are experimenting with new tools such as ChatGPT and DALL-E, and opinions tend toward the extremes: they are seen as either an unmitigated blessing or a curse. Yet there are some important implications of this new technology that have not been fully appreciated.
Methods for Evaluating AI Capabilities
As artificial intelligence (AI) expands its scope of applications across society, understanding its impact becomes increasingly critical. The OECD's AI and the Future of Skills (AIFS) project is developing a comprehensive framework for regularly measuring AI capabilities and comparing them to human skills. The resulting AI indicators should help policymakers anticipate AI’s impacts on education and work.
This volume describes the second phase of the project: exploring three different approaches to assessing AI. First, the project explored the use of education tests for the assessment by asking computer experts to evaluate AI’s performance on OECD’s tests in reading, mathematics and science. Second, the project extended the rating of AI capabilities to tests used to certify workers for occupations. These tests present complex practical tasks and are potentially useful for understanding the application of AI in the workplace. Third, the project explored measures from direct AI evaluations. It commissioned experts to develop methods for selecting high-quality direct measures, categorising them according to AI capabilities and systematising them into single indicators. The report discusses the advantages and challenges in using these approaches and describes how they will be integrated into developing indicators of AI capabilities.
Integrating AI into higher education is not a futuristic vision but an inevitability. Colleges and universities must adapt and prepare students, faculty, and staff for their AI-infused futures.
Upon its release in late 2022, ChatGPT has brought a seismic shift in the entire landscape of AI, both in research and commerce. Through instruction-tuning a large language model (LLM) with supervised fine-tuning and reinforcement learning from human feedback, it showed that a model could answer human questions and follow instructions on a broad panel of tasks. Following this success, interests in LLMs have intensified, with new LLMs flourishing at frequent interval across academia and industry, including many start-ups focused on LLMs. While closed source LLMs (e.g., OpenAI’s GPT, Anthropic’s Claude) generally outperform their open-source counterparts, the progress on the latter has been rapid with claims of achieving parity or even better on certain tasks. This has crucial implications not only on research but also on business. In this work, on the first anniversary of ChatGPT, we provide an exhaustive overview of this success, surveying all tasks
where an open-source LLM has claimed to be on par or better than ChatGPT.
Via Edumorfosis, juandoming
The emergence of generative artificial intelligence (AI), while creating new possibilities for learning and teaching, has exacerbated existing assessment challenges within higher education. However, there is considerable expertise, based on evidence, theory and practice, about how to design assessment for a digital world, which includes artificial intelligence. AI is not new, after all, even if the current iterations of generative AI are. This document, constructed through expert collaboration, draws on this body of knowledge and outlines directions for the future of assessment. It seeks to provide guidance for the sector on ways assessment practices can take advantage of the opportunities, and manage the risks, of AI, specifically generative AI.
Medical AI has transformed modern medicine and created a new environment for future doctors. However, medical education has failed to keep pace with these advances, and it is essential to provide systematic education on medical AI to current medical undergraduate and postgraduate students. To address this issue, our study utilized the Unified Theory of Acceptance and Use of Technology model to identify key factors that influence the acceptance and intention to use medical AI. We collected data from 1,243 undergraduate and postgraduate students from 13 universities and 33 hospitals, and 54.3% reported prior experience using medical AI. Our findings indicated that medical postgraduate students have a higher level of awareness in using medical AI than undergraduate students. The intention to use medical AI is positively associated with factors such as performance expectancy, habit, hedonic motivation, and trust. Therefore, future medical education should prioritize promoting students’ performance in training, and courses should be designed to be both easy to learn and engaging, ensuring that students are equipped with the necessary skills to succeed in their future medical careers.
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Knowing How Technology and Artificial Intelligence Have — and Have Not — Affected Jobs in Recent Decades Offers Insight into How They Could Affect the Future of Work
The arrival of AI-powered chatbots has made many people think once again about the skills needed for the "digital future of work." Any efforts to improve digital skills are addressing a moving target, which implies that teaching the appropriate skills is not a trivial matter. What is certain, though, is that there is a very considerable digital skills gap between richer and poorer countries.
The demand for digital skills is very heterogeneous, ranging from basic digital literacy that enables individuals to effectively use simple digital tools to the advanced digital skills necessary to participate in the “global division of digital labour.”
The limited data available suggest that levels of digital literacy are relatively low in countries of the Global South. Low-income countries exhibit extremely low levels of digital literacy, while the gaps between middle-income and high-income countries are also very considerable.
The evidence on the use of digital technologies in schools suggests that most middle-income countries lag far behind high-income countries, particularly in schools with students with low socio-economic status. This may cause digital skills gaps to persist or even grow.
Digital skills training programmes are proliferating, without having proven their effectiveness in terms of enhancing digital skills.
Some evidence indicates that job referrals or training in the use of professional online platforms may be as important as digital training in improving employment prospects.
Proponents of AI say that tools like ChatGPT will bring significant benefits. It can assist teachers, personalize learning with AI-powered tutoring systems and automate administrative tasks, allowing educators to focus more on teaching and mentoring students. However, current educational challenges in access, equity and inclusion in education can be significantly magnified by digital exclusion, lack of connectivity and the digital readiness of countries. On top of these challenges, we have many education systems still attached to teaching methods based on memorization, lack of relevance and engagement as well as poor and short-sighted standardized assessments that can hamper the effective integration of AI for an inclusive and quality education.
Artificial intelligence (AI) and robotics are major breakthrough technologies that are transforming the economy and society. The OECD’s Artificial Intelligence and the Future of Skills (AIFS) project is developing a programme to assess the capabilities of AI and robotics, and their impact on education and work. This volume reports on the first step of the project: identifying which capabilities to assess and which tests to use in the assessment. It builds on an online expert workshop that explored this question from the perspectives of both psychology and computer science. The volume consists of expert contributions that review skills taxonomies and tests in different domains of psychology, and efforts in computer science to assess AI and robotics. It provides extensive discussion on the strengths and weaknesses of different approaches, and outlines directions for the project. The report can therefore be a resource for the research community of multiple fields and policy makers who wish to obtain deeper insight into the complexity of machine capabilities.
Abstract:
In this paper, we show the causal influence of the launch of generative AI in the form of ChatGPT on the search behavior of young people for apprenticeship vacancies. There is a strong and long-lasting decline in the intensity of searches for vacancies, which suggests great uncertainty among the affected cohort. Analyses based on the classification of occupations according to tasks, type of cognitive requirements, and the expected risk of automation to date show significant differences in the extent to which specific occupations are affected. Occupations with a high proportion of cognitive tasks, with high demands on language skills, and those whose automation risk had previously been assessed by experts as lower are significantly more affected by the decline. However, no differences can be found with regard to the proportion of routine vs. non-routine tasks.
With rapid progress in natural language processing and image generation, AI now affects creative occupations, which were previously considered safe from automation. Cecily Josten and Grace Lordan write that job displacement concerns are legitimate and new approaches to education and workforce development are needed. They say that addressing biases in AI and fostering reskilling are also necessary for inclusive adaptation to AI advancements.
rtificial Intelligence (AI) has been the talk of the town, promising transformative learning experiences. However, for many learning and development professionals, the path from understanding the potential of AI to practically integrating it into eLearning remains unclear. This session, titled "Beyond the Buzzwords: Practical Steps to Integrate AI in eLearning," offers the roadmap to demystify this journey.
In this engaging session, attendees will first gain a high-level understanding of AI's potential in the eLearning landscape. This foundational knowledge will serve as the basis for the more practical, hands-on exploration of AI integration strategies. Participants will learn the key considerations when planning AI implementation, such as selecting the appropriate eLearning content for AI enhancement, understanding the technical prerequisites, and navigating potential challenges that may arise during the process.
By the end of the session, attendees will have a clear roadmap to embark on their own journey of AI integration in eLearning, equipped with practical knowledge, strategies, and inspiration.
Key Learning Objectives:
Understand the transformative potential of AI within the eLearning landscape and its ability to enhance learner engagement and personalize learning experiences
Learn about practical strategies and considerations for integrating AI into eLearning modules
Gain insights into navigating potential challenges that may arise during the AI implementation process
See real examples of AI-enabled eLearning, offering context and understanding of AI's utility
Gain confidence and practical knowledge to embark on your own journey of AI integration in eLearning
Artificial intelligence (AI) and robotics are major breakthrough technologies that are transforming the economy and society. The OECD’s Artificial Intelligence and the Future of Skills (AIFS) project is developing a programme to assess the capabilities of AI and robotics, and their impact on education and work. This volume reports on the first step of the project: identifying which capabilities to assess and which tests to use in the assessment. It builds on an online expert workshop that explored this question from the perspectives of both psychology and computer science. The volume consists of expert contributions that review skills taxonomies and tests in different domains of psychology, and efforts in computer science to assess AI and robotics. It provides extensive discussion on the strengths and weaknesses of different approaches, and outlines directions for the project. The report can therefore be a resource for the research community of multiple fields and policy makers who wish to obtain deeper insight into the complexity of machine capabilities.
hatGPT, which stands for Chat Generative Pre-trained Transformer, is a text-generating AI chatbot developed by OpenAI and launched on November 30, 2022. This briefing examines the influence of ChatGPT usage on organizations and workers.
Which roles are most impacted by using ChatGPT and which are the least impacted? For which skill does generative AI have the largest organizational implications? Are there concerns about ChatGPT’s safety and security and, if so, how should they be addressed?
Read the issue briefing to get our full analysis.
Artificial Intelligence–AI–has been around a long time, but caught everyone’s attention with the launch of generative AI, ChatGPT, and DALL-E. These made using AI easy enough for …
The global talent gap is long-lamented and continues to grow — in the U.S. alone, there are currently 9.6 million job openings compared to 6.5 million unemployed.
This has many calling for upskilling and re-skilling of existing workforces. However, while many business leaders recognize that need, they are hampered by a lack of time, resources and funds to develop materials on which to train their workers.
This is another area that — like so many others — where generative AI offers transformative promise, according to Cypher Learning. The learning management system provider released a study this week exploring leaders’ challenges with upskilling, their exploration of gen AI in building training materials and the promise the technology holds in repairing the schism between the number of workers and available jobs.
“Generative AI is already transforming employee training,” CYPHER Learning founder and CEO Graham Glass told VentureBeat. “In 2024, the focus will be on reimagining education with AI at its core.”
In the evolving landscape of education, one topic has taken center stage: generative AI. As educators, we tend to be on a continuous quest for innovative edtech tools that will enhance the learning experience for students. The potential of generative AI is both promising and profound, but it raises critical questions: How can this transformative technology be harnessed not only to educate but to empower inclusively and equitably?
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