The Promise of Personalized Learning Never Delivered. Today’s AI Is Different

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Over the last decade, educators and administrators have often encountered lofty promises of technology revolutionizing learning, only to experience disappointment when reality failed to meet expectations. It’s understandable, then, that educators might view the current excitement around artificial intelligence with a measure of caution: Is this another overhyped fad, or are we on the cusp of a genuine breakthrough?

A new generation of sophisticated systems has emerged in the last year, including Open AI’s GPT-4. These so-called large-language models employ neutral networks trained on massive data sets to generate text that is extremely human-like. By understanding context and analyzing patterns, they can produce relevant, coherent and creative responses to prompts. 

Based on my experiences using several of these systems over the past year, I believe that society may be in the early stages of a transformative moment, similar to the introduction of the web browser and the smartphone. These nascent iterations have flaws and limitations, but they provide a glimpse into what might be possible on the very near horizon, where AI assistants liberate educators from mundane and tedious tasks, allowing them to spend more time with students. And this may very well usher in an era of individualized learning, empowering all students to realize their full potential and fostering a more equitable and effective educational experience.

There are four reasons why this generation of AI tools is likely to succeed where other technologies have failed:

1. Smarter capabilities: These AI systems are now capable of passing many standardized tests, from high school to graduate- and professional-level exams that span mathematics, science, coding, history, law and literature. Google’s Med-PaLM performed at an “expert” doctor level on the medical licensing exam, not only correctly answering the questions but also providing a rationale for its responses. The rate of improvement with these systems is astonishing. For example, GPT-4 made significant progress in just four months, going from a failing grade on the bar exam to scoring in the 90th percentile. It scored in the 93rd percentile on the SAT reading and writing test and the 88th on the LSAT, and got a 5 — the top score — on several Advanced Placement exams.
   
2. Reasoning engines: AI models like GPT-4, Microsoft’s Bing Chat, and Google’s Bard are advancing beyond simple knowledge repositories. They are developing into sophisticated reasoning engines that can contextualize, infer and deduce information in a manner strikingly similar to human thought. While traditional search engines functioned like librarians guiding users toward relevant resources, this new generation of AI tools acts as skilled graduate research assistants. They can be tasked with requests such as conducting literature reviews, analyzing data or text, synthesizing findings and generating content, stories and tailored lesson plans.
   
3. Language is the interface: One of the remarkable aspects of these systems is their ability to interpret and respond to natural language commands, eliminating the need to navigate confusing menus or create complicated formulas. These systems also explain concepts in ways people can easily understand using metaphors and analogies that they can relate to. If an answer is too confusing, you can ask it to rephrase the response or provide more examples.
   
4. Unprecedented scale: Innovations often catch on slowly, as start-ups must penetrate markets dominated by well-established companies. AI stands in stark contrast to this norm. With tech giants like Google, OpenAI and Microsoft leading the charge, the capabilities of large-language models are not only rapidly scaling, but becoming deeply integrated into a myriad of products, services and emerging companies.

These capabilities are finding their way into the classroom through early experiments providing a tantalizing sense of what might be possible.  

• Tutoring assistants: The capability of these systems to understand and generate human-like text allows for providing individualized tutoring to students. They can offer explanations, guidance and real-time feedback tailored to each learner’s unique needs and interests. Khan Academy and DuoLingo are also piloting GPT-4 powered tutors that have been trained on their unique datasets.
  
• Teaching assistants: Teachers spend hours on tedious administrative tasks, from lesson planning to searching for instructional resources, often at the cost of less time for teaching. As capable reasoning engines, AI can assist teachers by automating many of these tasks — including quickly generating lesson plan ideas, developing worksheets, drafting quizzes and translating content for English learners. 
  
• Student assistants: AI-based feedback systems have the capacity to offer constructive critiques on student writing, including feedback aligned to different assessments, which helps students elevate the quality of their work and fine-tune their writing skills. It also provides immediate help when students are stuck on a concept or project.

While these technologies are enormously promising, it is also important to recognize that they have limitations. They still struggle with some math calculations and at times offer inaccurate information. Rather than supplanting teachers’ expertise and judgment, they should be utilized as a supportive co-pilot, enhancing the overall educational experience. Many of these limitations are being addressed through integrations with other services, such as Wolfram for dramatically better math capabilities. Put another way, this is the worst these AI technologies will be. Whatever shortcomings they have now will likely be improved in future releases.

The unprecedented scale and rapid adoption of generative AI mean that these benefits are not distant possibilities, but realities within reach for students and educators worldwide. By harnessing the power of AI, it is possible to create a future where teaching and learning are not only more effective and equitable, but also deeply personalized, with students empowered to reach their full potential and teachers freed to focus on teaching and fostering meaningful connections with their students.

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