Artificial intelligence (AI) is revolutionizing nearly every other sector. Education is not uncommon. The integration of AI in education promises a more personalized, streamlined, and improved experience in learning and administration and better outcomes for education. Therein lies the promise of a bright and promising future in education, which also brings with it all issues and debates of tremendous ethical considerations. There ought to be hope and optimism among educators and policymakers about the potential of AI in education.
Nevertheless, there are a number of ethical issues that one needs to be mindful of, despite all the promises and possibilities of AI in education.
In this article, we shed light on those challenges.
Let us have a look:
Privacy and Data Security
One core issue of ethics in AI-based education involves the privacy and safety of students’ data. AI-based systems require large amounts of data to function effectively. Thus, vast amounts of information that touch upon the type of performances or behaviours put forward by a student, or even the student’s personal life, fall in the domain of focus. The data must be safely held and used only for education-based purposes. Data breaches and misuse are possible and very disastrous.
A data breach at ProctorU, an online proctoring service, in 2020 is one such big example. The personal information of over 440,000 students was leaked. This incident highlighted the vulnerabilities in data security within AI-driven educational tools.
Bias and Fairness
The more trained artificial intelligence is, the better its output will be. If the training data reflects biases, then the AI system will probably propagate these biases, and hence, it may project unfairness toward a specific group of students. Eliminating and portraying fair levels in AI algorithms are among the most difficult ones, especially those based on continuous scrutiny and updates, making educators and policymakers feel active and responsible for their roles.
According to a research by the National Institute of Standards and Technology (NIST), students of color had greater error rates from facial recognition algorithms employed in various educational products than did white students. In academic settings, this bias may also result in unfair treatment and discrimination.
Autonomy and Dependence
Autonomy and dependence are other graving concerns for both students and teachers. Though AI can provide personalized learning paths and instant feedback, there is a risk that students may become overly dependent on these systems, potentially hindering their ability to think critically and independently. Similarly, teachers might rely too heavily on AI tools for grading and assessment, which could undermine their professional judgment and expertise.
In 2019, the UK government faced backlash when an AI algorithm used to predict A-level results during the COVID-19 pandemic was found to unfairly devalue students from disadvantaged backgrounds. This incident underscored the importance of human oversight in AI-driven educational assessments, reassuring educators and policymakers about the irreplaceable role of human judgment in education.
Accountability and Transparency
In AI-driven learning systems, accountability becomes elusive and hard to pin down. Even in cases where the AI makes mistakes—such as grading a student’s assignment too low or providing false evaluation feedback—it might be challenging to determine who should be sued—the educational institution or the AI itself. Furthermore, AI systems’ algorithms are frequently opaque, leaving little opportunity for stakeholders to comprehend the decision-making philosophy behind them. Establishing clear lines of accountability and promoting transparency are essential for effectively fostering confidence in AI-powered education.
For example, the European Union’s General Data Protection Regulation (GDPR) includes provisions that require organizations to explain the logic behind automated decisions, which can help increase transparency in AI-driven educational tools.
Ethical Use of AI
However, putting that aside, educators and policymakers need to consider the ethics of AI in education. AI tools should augment human interaction and judgment rather than replace them, and all stakeholders, namely students, parents, and teachers, should be involved in planning how and when to apply AI tools in educational settings. Developing guidelines and frameworks in this landscape is exciting.
The UNESCO Recommendation on the Ethics of Artificial Intelligence, adopted in 2021, provides a global framework for the ethical use of AI, including in education. This recommendation emphasizes the importance of human rights, fairness, and transparency in AI applications.
This technology can thus change human approaches to learning, designed to suit the individual and efficient processes of its administration. What one has to bear in mind, however, are ethical concerns and issues surrounding AI-activated education. Concerns over privacy, bias, autonomy, accountability, and morality will all need to be addressed so that such education can be used responsibly and equitably.
