EdTech Insight – 10 ways to prevent shadow AI disaster

by | Jul 8, 2024 | CIO, News & Insights

Executive Summary and Main Points

The increasing use of unsanctioned Artificial Intelligence (AI) by employees in the workplace is leading to substantial data and security risks. Research by Cyberhaven reveals extensive unauthorized AI tool usage, with a staggering majority of cases not being through corporate accounts, thereby exposing sensitive data to external AI platforms. Employees are drawn to AI to enhance productivity and avoid obsolescence, but this shadow AI introduces a plethora of risks including legal liabilities, data leakage, unfair workforce advantages, and the potential compromise of proprietary data. Steps to counter such risks include establishing acceptable AI use policies, raising awareness on AI risks, blocking access to certain AI tools, and providing adequate AI training.

Potential Impact in the Education Sector

The trends observed in unauthorized AI use in corporate settings could have similar repercussions within the Education sector, specifically in Further Education, Higher Education, and for Micro-credentials. Shadow AI could disrupt academic integrity, compromise the privacy of student records, and inadvertently allow for cheating and plagiarism if not regulated. Strategic partnerships, such as with AI service providers, and digitalization processes can help higher education institutions harness AI’s potential responsibly, while mitigating risks by implementing robust IT frameworks, engaging in thorough vetting of AI technologies, and monitoring tool usage on-campus to ensure compliance with data governance and privacy laws.

Potential Applicability in the Education Sector

AI and digital tools can be tailored to enhance global education systems through personalized learning aids, automated administrative tasks, and advancement in research capabilities. AI-driven analytics could be employed for curriculum development, assessing student performance, and identifying learning gaps. Moreover, AI-powered virtual assistants can provide on-demand tutoring and language support, facilitating a more inclusive and accessible learning experience for students from diverse backgrounds. AI can also assist in handling voluminous tasks such as admission processes or grading, allowing educators more time to focus on teaching and mentoring.

Criticism and Potential Shortfalls

Despite the benefits, unregulated AI adoption in the educational sphere raises critical ethical and cultural considerations. For instance, reliance on AI for grading or generating educational material could lead to homogenization of content, marginalizing diverse perspectives. There is also a significant risk of AI inheriting biases from training data sets, potentially perpetuating stereotypes or discriminative practices. Comparatively, international case studies may reveal disparate impacts of AI in education influenced by varying data protection laws and educational norms. It is crucial for institutions to establish transparent oversight for AI use to maintain academic integrity and uphold privacy standards.

Actionable Recommendations

For higher education leaders, it is imperative to implement a strategic framework to leverage AI technology effectively. This includes:

1. Developing an institution-wide acceptable use policy for AI tools to delineate clear guidelines and expectations.

2. Conducting regular training and awareness programs on AI risks and ethical use for both faculty and students.

3. Forming strategic partnerships with vetted AI providers to ensure adherence to data security and privacy regulations.

4. Creating innovation hubs within institutions where AI can be explored safely under institutional oversight.

5. Investing in robust IT infrastructure that can withstand the introduction and use of AI, with strong data protection and monitoring systems.

By guiding AI use through strategic policy and technological frameworks, educational institutions can foster innovation while minimizing potential risks

Source article: https://www.cio.com/article/2150142/10-ways-to-prevent-shadow-ai-disaster.html