“a set of competencies that enables individuals to critically evaluate AI technologies; communicate and collaborate effectively with AI; and use AI as a tool online, at home, and in the workplace (Long & Magerko, 2020).”
This set of competencies has alternately been described as having four main capabilities: “application, authenticity, accountability, and agency (Cardon, Fleischmann, Aritz, Logemann & Heidewald, 2023)."
Application: understanding how to match and use AI tools for a specific task.
Authenticity: focus on genuine human communication.
Being AI Literate does not mean you need to understand the advanced mechanics of AI. It means that you are actively learning about the technologies involved and that you critically approach any texts you read that concern AI, especially news articles (Harvard, 2024).
Accountability: taking responsibility for the use and communication of AI generated and influenced content.
Agency: the retention of human control while utilizing generative AI.
Efficiency, Productivity, and Innovation Across Industries: Generative AI not only automates routine tasks and complex computations but also drives innovation in fields such as healthcare, environmental science, art, and engineering, leading to breakthroughs and new methodologies.
Personalization and Enhanced User Experiences: By understanding individual preferences, AI tailors experiences in marketing, entertainment, education, and healthcare, offering customized content, recommendations, and treatments that significantly improve engagement and outcomes.
Advanced Data Analysis for Informed Decision-Making: AI excels in processing vast amounts of data to uncover insights, supporting critical decision-making in healthcare, finance, scientific research, and climate modeling, thereby facilitating progress and precision in various fields.
Breaking Down Language Barriers and Fostering Global Communication: AI-driven translation and language processing services enhance international communication, making education, business, and diplomacy more inclusive and effective.
Improving Accessibility and Healthcare: AI technologies offer support for individuals with disabilities through adaptive devices and interfaces, revolutionize healthcare with diagnostic accuracy, personalized treatment plans, and assistance in complex surgeries.
Enhancing Education and Environmental Sustainability: In education, AI enables personalized learning paths and interactive tools, while in environmental management, it optimizes resource use, monitors ecosystems, and predicts climate-related events, contributing to more sustainable development practices.
Enabling Smarter Business Strategies and Market Insights: Generative AI analyzes market trends, predicts consumer behavior, and optimizes supply chains, helping businesses to innovate and adapt to changing market dynamics efficiently.
Strengthening Safety, Security, and Public Welfare: Through improved cybersecurity measures, enhanced public safety protocols, and efficient disaster response, AI plays a crucial role in protecting information, individuals, and communities.
Cultivating Creativity and Expanding the Arts: By providing tools that assist in the creation of art, music, literature, and digital experiences, AI opens up new avenues for creativity and artistic expression, democratizing the arts and enabling new forms of collaboration.
Fostering Scientific Discovery and Research Efficiency: AI accelerates the pace of research across disciplines, from drug discovery and genomics to physics and cosmology, by enabling faster simulations, data analysis, and the exploration of hypotheses that would be impractical for humans to investigate alone.
Reliability, Transparency, and Misinformation: Challenges in ensuring AI-generated content is accurate and transparent, combined with the risk of spreading misinformation, necessitate rigorous verification methods and ethical guidelines in research.
Bias, Equity, and Cultural Impacts: The reflection and perpetuation of human biases in AI, along with the dominance of certain languages and cultures, pose significant challenges for creating inclusive and equitable AI systems. Researchers must consider the societal and cultural impacts of AI on diverse communities.
Privacy and Data Security: The management and protection of sensitive data by AI platforms are paramount, requiring research into advanced security protocols and ethical data handling practices.
Intellectual Property and Ethical Use: The use of existing content by AI raises intellectual property issues, and the potential for unethical applications, such as deepfakes, demands a focus on developing ethical AI frameworks.
Access Inequality and Economic Impacts: The digital divide created by access inequality to AI tools and the potential job automation by AI call for research into equitable access and the socioeconomic implications of AI deployment.
Environmental Sustainability: The environmental footprint of training and deploying AI models requires research into more sustainable AI practices and technologies.
Regulatory, Legal, and Ethical Frameworks: Developing comprehensive legal and ethical frameworks to govern AI use and ensure accountability, consumer protection, and fair competition is a critical area for interdisciplinary research.
Accessibility and Inclusivity: Ensuring AI tools and technologies are accessible to individuals with disabilities is essential, requiring research into inclusive design practices.
Psychological and Societal Dynamics: The psychological effects of AI interactions and AI's impact on societal norms and human behavior necessitate multidisciplinary research into the human-AI relationship.
Global Governance and Technological Equity: Addressing the concentration of AI power and development, and ensuring equitable access to AI technologies across the globe, calls for international cooperation and research into global governance models.
