AI is revolutionizing fields like education, but the challenge remains maintaining the human element and addressing accountability concerns.
2023 has been quite a year for artificial intelligence (AI) adoption. That’s been driven by the increasing availability and awareness of generative AI (GAI) tools like ChatGPT.
In a recent study “AI in education: where we are and what happens next”, Oxford University Press points out “GAI is not the first digital technology to disrupt education, nor even the first instance of AI making its way into the classroom.”
It wasn’t too long ago that the concern was that students were copying answers from Wikipedia. Now, and more positively, platforms like Kahoot! use AI to create interactive quizzes and games that help students learn and retain information more effectively.
According to the study, “63% of schoolteachers and 59% of English language teachers we surveyed believe that digital resources, including AI technology, have already had a positive impact on educational outcomes for their students.”
They conclude, “AI is already changing both classroom and independent learning. But the research gathered here underlines the principle that education should always drive technology—not the other way around.”
So, what are the benefits and risk of AI in education, and what can we do about it?
Benefits of AI in Education
Artificial Intelligence has the potential to transform education in several positive ways. One of the most significant advantages is the ability to provide personalized learning experiences.
AI systems can analyze individual students’ strengths and weaknesses, tailoring educational content and pacing to suit each student’s needs. This individualized approach can lead to improved learning outcomes and increased student engagement.
AI can also significantly enhance the efficiency of educational processes. It can automate administrative tasks, like grading and scheduling. That allows educators to focus more on teaching and less on paperwork. This efficiency can result in time and cost savings for educational institutions.
Accessibility is another area where AI can make a substantial impact. AI-powered tools can provide support for students with disabilities, such as speech-to-text and text-to-speech conversion, making educational content more inclusive and accessible to a wider range of learners.
Furthermore, AI’s data analytics capabilities can provide valuable insights into student performance. By collecting and analyzing data, AI can help educators identify areas where students may be struggling and enable data-driven decision-making to enhance teaching methods and curriculum development.
AI also offers the advantage of 24/7 availability. Educational resources and tools powered by AI can be accessed at any time and from virtually anywhere, allowing for greater flexibility in learning.
Lastly, AI can be a valuable tool for language learning. It can provide real-time pronunciation feedback, assist with vocabulary acquisition, and facilitate conversational practice, making language learning more effective and engaging.
Risks and Challenges of AI in Education
While AI holds great promise in education, it also presents several challenges and potential risks. One of the primary concerns is related to privacy. The collection and analysis of student data raise significant privacy issues, as sensitive information may be at risk of misuse, breaches, or unauthorized access.
Another major concern is bias and fairness. AI systems can inherit biases from their training data, which may result in discriminatory outcomes. This can lead to disparities in educational experiences and opportunities, disadvantaging certain groups of students.
There is also apprehension regarding teacher displacement. As AI automates administrative tasks and, in some cases, instructional tasks, there is a fear of job displacement among educators. While AI can complement and enhance teaching, it should not replace the crucial human element in education.
The quality of AI-generated educational content is another issue. Not all content produced by AI is of high quality, and there is a risk that subpar materials may find their way into educational settings, potentially compromising the learning experience.
The digital divide is a significant concern. Not all students have equal access to technology and the internet. Overreliance on AI in education could exacerbate educational inequalities, creating disparities in access to quality learning resources.
The depersonalization of education is another risk. Excessive reliance on AI can lead to a one-size-fits-all approach that may not suit every student’s learning style. The human touch, such as emotional support and social interaction, may be diminished in such a scenario.
Accountability is also an issue. If educators rely too heavily on AI, it may become challenging to assign responsibility when something goes wrong or when there are educational failures.
The integration of AI in education has the potential to be transformative, but it must be approached with caution. It’s crucial to consider the potential benefits while addressing the risks and challenges.
Ethical considerations, careful planning, and ongoing involvement of educators and stakeholders are essential to maximize the positive impact of AI in education while mitigating potential drawbacks.
Role of LSPs in AI for Education
As we like to say around here, AI innovations are only as good as the data they learn from. And that data is only useful if it goes through a meaningful annotation process.
The linguist was at the core of translation until machine translation came long. As a result, language service provider began to shift from being language experts to being language AND technology experts.
Roles previously held by tech employees like data engineers and solutions architects are now commonplace at LSPs.
LSPs now have first-hand experience with the challenges of developing AI technology as well as the necessary technical experts in-house to support and develop these innovations and the technology necessary for data solutions.
What we’ve learned over the years is you need a balance of automated and human assisted data collection. The tools are out there to gather large swaths of data, but humans still rule with respect to interpreting exactly what you need in the context of your innovation.
What you need is specialized, human-assisted data collection and not an all-encompassing, quick solution. This saves you money in the long run and gets you exactly what you need.
Partner With Us
As a language solutions provider in the data for AI space, we highlight all the ways we can customize your datasets while also steering you towards the most effective and price-conscious collection option for your solution.
Contact us today to start working together.
