This AI Literacy Review explores a machine learning game for kids and families, algorithmic literacy for at-risk populations, AI as a necessary new skillset, Australians and AI usage, libraries’ role in AI literacy, AI impact on college writing classes, young people’s perspectives on AI at school, a create-your-own-ChatGPT learning activity, and more!
General
Ellia Yang, Amy Ogan, Jessica Hammer, and Jaemarie Solyst present a poster at a conference on computing education research titled Designing an AI Literacy Transformational Game for Families, in which they designed a game to support youth and families to learn about machine learning and algorithmic bias. They concluded that the game enabled families to discuss serious topics such as bias and helped youth grasp some of the nuance in data labeling in AI.
Community leaders in Guatemala receive training to enhance algorithmic literacy among at-risk populations through an initiative from the Asociación COMUNICARES and DW Akademie. Called Algoritmo A Mi Ritmo (Algorithm Matches my Rhythm), the training initiative aims to introduce algorithmic literacy to school teachers and local communicators for them to pass it on to youth.
In Why Social Science is Vital to Developing Ethical AI, Laura Varley interviews Cecilia Danesi, a University of Salamanca professor in AI and civil law, who sees the importance of the cross-section of AI and the social sciences. Danesi sees an issue when programmers and engineers working on AI lack training in AI ethics, and believes AI literacy is very important for them as well as users.
Microsoft and Accenture’s report New Zealand’s Generative AI Opportunity examines the economic opportunities that Gen. AI presents, looking at 19,000 tasks across 400 jobs to see how people might improve their productivity through Gen. AI. The report identifies “Skilled workforces” as one of six key enablers to NZ realizing the benefits of Gen. AI, which includes executives knowing how it can be deployed and workers having the digital literacy skills to make use of it. The report cites Microsoft and LinkedIn’s 2024 Work Trend Index Annual Report showing that 84% of knowledge workers in NZ use Gen. AI at work, but most are using their own Gen. AI tools, not ones provided by their organization.
Organizations
Cal Al-Dhubaib in A Helpful Guide To AI’s Impact On The Workforce in Forbes discusses how workforce literacy has changed over the decades, first encompassing digital literacy in word processing and spreadsheet software, to data literacy in Power BI, and now requiring AI literacy so staff know when to trust outputs and how to identify tasks to be augmented by AI. He says successful organizations are adopting programs to train workers on AI proficiency and safety, using educational resources such as key books on AI, and investing in AI literacy programs and AI councils across the organization.
The ADP Research Institute’s People at Work 2024: A Global Workforce View report of 34,000 workers across 18 countries found that 43% of workers thought having AI on the job would be a good thing. Only 47% felt their employer invests in the skills they need to advance, and nearly half agreed that tech will be considered a necessary skill set in the future.
Reported by Finbarr Toesland in AI Success Limited by Lack of Skills and Governance Issues, a survey of CIOs at large companies in the UK found that 40% are concerned about how to train staff on using AI. There is also a challenge with the move to remote working in terms of AI ethics and best practices.
In the UK, learning disability charity Mencap is partnering with tech company Multiverse to offer apprenticeship programs in data and digital skills. One of the programs will be the 13-month AI for Business Value, and programs will help develop staff’s skills in AI and data literacy.
In The AI Literacy Movement | In Conversation with Jeanne Meister, HR consultant Meister looks at whether companies are doing enough to equip staff with skills and confidence to use AI. She points to fear and uncertainty making companies not take AI literacy seriously enough, and recommends building awareness and trying to create a movement, rather than thinking a one-time course will be enough. She categorizes the skills needed into three areas: technical, human power, and higher-order cognitive skills, and says the key is to engage learners, regardless of what type of learning is offered.
Libraries
Trish Hepworth of the Australian Library and Information Association writes about new research showing a critical need for adult media literacy support in Australia and what the role of libraries could be in helping people with digital and AI skill-building. The Adult Media Literacy in 2024: Australian Attitudes, Experiences and Needs report by Tanya Notley, Simon Chambers, Sora Park, and Michael Dezuanni found very little change in Australians’ confidence in their digital media abilities compared to 2021, and also found that 82% of respondents see an immediate need for media literacy programs for adults. Respondents were asked specifically about Generative AI and around one-third to one-half wanted to learn more about how to use new technologies such as Gen. AI, with the interest depending on their age bracket, education level, and household income. There was also a gender gap found, with women 12% less likely to have used text-focused Gen. AI than men, and 15% less likely to have used image-focused Gen. AI. Hepworth writes about how library and community spaces can provide assistance in the AI literacy area and calls for government investment in a national solution for Australia. (see Trish Hepworth’s LinkedIn post)
In Why Understanding ChatGPT Logic Can Help Create a Foundation for AI Literacy at the 2024 Lifelong Information Literacy Conference, Kirk Bowman advocates for teaching how it works, not just what it works for. For librarians, this means understanding it, applying it to existing information literacy teaching skills, and practicing. (find the full list of conference sessions and links to recordings)
Education
In AI Cheating Is Getting Worse. Colleges still don’t have a plan in The Atlantic, Ian Bogost reports on how college writing instructors are coping (or not) with the onslaught of AI tools and ease of generating text with ChatGPT. One person interviewed, John Warner, a former college writing instructor and author of a new book on writing in the age of AI, says that part of the problem is that college papers themselves tend to follow a rigid format that is easy for AI to generate. Another, Hollis Robbins of University of Utah, is quoted as saying, “If you’re a lit professor and still asking for the major themes in Sense and Sensibility, then shame on you.”
Elon University and the American Association of Colleges and Universities publish the free digital guidebook A Student Guide to Navigating College in the Artificial Intelligence Era with the goal of spreading AI literacy in core college education. It includes visual aids such as icons and examples of prompts and use cases.
The Youth Advisory Council for the National Association for Media Literacy Education’s document Youth Perspectives on AI in the Classroom promotes the idea that students can use AI in a healthy way when paired with media literacy skills, and discusses ways that teachers in the U.S. are using it in the classroom.
Walsh University launches an AI-focused Skilled Technical Workforce (STWF) Program to foster skills for educators and administrators to integrate AI into K-12 education.
Ema Roloff in the TikTok/YouTube video AI Literacy in Schools? raises the question of how will schools teach AI readiness when they’ve already stopped teaching how to type and other basic software skills, leaving people unprepared for modern office environments.
Pace AI’s ESL Educator’s AI Literacy Course – Lesson 1 – A Brief History of AI YouTube video offers a 9-minute introductory lesson aimed at educators about the history of AI, making reference to science fiction, historical fears about technology, and examples of AI.
João Gonçalves and Sarah Young post the assignment Create Your Own ChatGPT for undergraduate students to gain a better understanding of how large language models are trained and improve students’ AI literacy. The assignment only requires a Google account to use the free Google Colab cloud environment, and a walk-through video is provided.
