Generative AI presents an opportunity to break away from old ways of thinking and redefine equity and how we serve students and communities.

Generative AI can enhance equity of access and attainment


Generative AI presents an opportunity to break away from old ways of thinking and redefine how we serve students and communities

Key points:

It took 10 years for PCs to reach 100 million users. It took seven years for the internet to achieve this milestone. Yet ChatGPT, the most widely-used form of generative artificial intelligence, reached 100 million users in less than six months. Almost one year since ChatGPT’s public debut, awareness of this immensely powerful technology is becoming mainstream, and conversations around the implications for higher education are taking shape.

The timing of this type of technological disruption could not be more opportune. Institutions of higher education have faced increased scrutiny over the last decade, making the urgency to increase access and student success more pronounced than ever. Generative AI presents a unique opportunity to both democratize and personalize access to learning and skill development at levels previously deemed impossible. With the introduction of generative AI, and without neglecting or minimizing the concerns, we have a potentially powerful means of addressing the rising tide of concerns around higher education’s value and role in the fabric of American society and economy.

Unfortunately, aspects related to academic integrity and fears of widespread cheating have largely dominated conversations around generative AI both on and off campuses. It also does not help that popular culture has long played into the public’s fears of a total robot takeover. These narratives, combined with a general (and understandable) sense of uncertainty around learning and critical thinking, obscure other important conversations that warrant greater attention.

So perhaps it is not surprising that rather than remain open minded to the transformative potential of generative AI, most gut reactions to ChatGPT in higher education double down on fear-based narratives.

In response, the edtech market has become bloated with AI detection tools that are currently incapable of accurately detecting generative AI. Not only are these tools largely ineffective, but the risk of doing harm by falsely accusing a student of academic dishonesty is tremendous.

We believe that it is time to turn our attention to the seemingly infinite potential of applications of GAI that provide unimaginable opportunities to positively transform the future of teaching and learning. Rather than provide an exhaustive list, we highlight just a few that have the potential to address the challenges of scarcity of access, institutional capacity, and attainment, thereby taking steps in addressing some current inequities.

  • Tutoring: AI-enabled tutoring platforms can ensure that all students have access to assistance, 24/7/365, enabling the learner to receive support when needed, rather than limiting tutoring to an instructor’s schedule.
  • Adaptive learning: AI-enabled adaptive learning platforms could provide support at scale, building on a learner’s strengths rather than starting from an assumption of common deficit. AI can calibrate language levels to ensure the student masters the concepts and competencies, creating personalized paths to learning regardless of the student’s socioeconomic resources.
  • Engagement platforms: AI-enabled platforms for engagement could enable proactive and “just-in-time” intervention so that learners are provided additional examples and knowledge. By generating alerts based on student progress, we can personalize the rate at which students proceed, but also provide encouragement and guidance. These platforms have extra potential when coupled with online AI-based tutoring for students who identify as first-generation, lower income, and for whom English is not the first language.
  • Translation and grammar: AI-enabled language/translation and grammar tools can allow students to focus more on learning content and language skills. We envision these tools allowing students to better express their proficiency in the subject regardless of their proficiency in grammar or language.
  • Brainstorming: AI-based platforms could be used by students to better hone arguments and context through serving as a “sounding board” and/or helpful “friend,” providing initial feedback that assists the learner in formulating and expressing their response, again alleviating inequities of holistic support scaffolding available to those with resources.
  • Holistic support: AI tools can provide a range of support material and mechanisms of interaction that are focused on learners who are neurodiverse, multilingual, and/or who face other challenges. This is critical in enhancing equity of opportunity for these populations who are currently underserved, at best, and not served at all, at worst.
  • Immersive learning: AI-integrated AR/VR and XR platforms could provide tremendous socio-cultural immersive exposure for learners for whom study abroad and even visits to museums, art galleries etc. may have been restricted in the past because of resource constraints. These not only provide greater context for learning, but have been shown to increase success rates through the enhancement of enquiry and discovery as a part of the learning process, moving away from rote learning mechanisms.

The rapid rise in AI-based technologies raises important considerations about our approach to AI going forward:

AI reveals our opportunities for improvement: Our fears around academic integrity merely highlighted something we already know–traditional assessment methods that value rote skills are not holistic barometers of student learning. We must acknowledge that students have always been able to cheat on assessments if they could afford it or could track down material online.

We need to play an active role in edtech design: Edtech products are generally not born out of thin air. Most elite universities have the resources to develop AI-based tools themselves and/or be engaged at a high level with private vendors in the development of next-generation platforms and tools. Yet, other universities and colleges, especially those serving the most under-resourced populations, do not have these resources and access to major AI developers. The implication here is that a small segment of the student population might benefit leaving out the majority or that the tools are created without the specific context needed to serve the larger population.

Institutions of all types must proactively explore AI or risk worsening inequity: If AI-based learning and student support resources are available only to a few select institutions, we might miss our opportunity to remedy current inequities in our education system. Even worse, current inequities might be further amplified if training datasets are not updated to challenge historical inaccuracies and biases, and if algorithms are not validated to remove unintended bias. Just as with the digital divide, we need to focus on creating equity and access rather than furthering educational deserts.

We cannot predict the future of generative AI in higher education or the possible opportunities or problems it might create, but we can balance our fears with a healthy dose of optimism and by focusing on new opportunities to address the problems within our industry. In doing so, we envision a world where institutions increase postsecondary access and attainment at a national level, while providing individualized paths and levels of support heretofore not possible.

It is time for a paradigm shift in higher education, and we suggest that generative AI presents the perfect opportunity to break away from our old ways of thinking and redefine how we serve our students and our communities. While continuing to emphasize the need to ensure appropriate development and addressing of critical concerns related to the increasing use of AI, we propose a fundamental change in how we approach this era of technological innovation by changing the common refrain of “What if generative AI creates {insert problem here}?” to “What if generative AI creates {insert opportunity here}?” If we want to create the change that we believe generative AI is capable of in higher education, we must become active participants in shaping this new reality, not passive consumers. We need to increase our engagement with partners in edtech, highlighting not just aspects of concern, but also those that could be transformative.

It is time to hold our adoption and development of AI to a higher standard. We must approach this moment not from a place of irrational fear but instead with the level of thought, rigor, and innovation that has been the hallmark of American leadership in higher education throughout the last century.

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