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Many were taken by surprise by the emergence of highly-sophisticated large language models. Notice was taken last year with OpenAI GPT-3. I was amazed last August, when I first asked GPT-3 to write a sample article about the impact of GPT on higher education. It responded with an accurate, cogent 700-word piece in just seconds. I wrote then that “higher ed will never be the same!” However, the models and interfaces continued to improve with the GPT-3.5 and ChatGPT. We have now embarked on an ever-accelerating improvement of the technology, fueled by tens of billions of dollars of investment and a hot competition most notably between Microsoft/Bing and Alphabet/Google. This will play out through the rest of 2023 and beyond.

No field is more likely to be affected by these advances than higher education. The ability to generate text, images, music, and other media with clarity, accuracy, and adaptability is on target to enhance the way in which we deliver learning and facilitate access to knowledge. A revolution is underway, and I can guarantee that it will touch your workplace in 2023 and beyond.

What can we expect? Some technological improvements will be noticeable by next month as GPT-4 is scheduled to be released. Those improvements will certainly be impressive. Faster, smoother, fewer lapses, and multi-modal models are expected to emerge with GPT-4. All the while, the algorithms will get smarter with ever-larger knowledge bases and even more than the 175 billion parameters of GPT-3. Equally impressive will be the variety of applications and interfaces that emerge. These will be accelerated in part by the race between Microsoft/OpenAI and Alphabet/Google with a variety of emerging applications.

Owen Yin of Medium got an early preview of Microsoft’s integration of ChatGPT technology into the search engine Bing. Expected to be formally released in coming weeks, Yin described some of the features of the GPT-enhanced search engine:

Microsoft is positioning it as an evolution of the search engine, asking you to think of it as a “research assistant, personal planner, and creative partner at your side. The integration will be powered by OpenAI’s GPT-4, a faster version of ChatGPT. Unlike ChatGPT, which is trained on data collected up to 2021, the new Bing will be able to access current information. When you ask a question, the AI will interpret it and make several searches related to your request. It will then compile the results and write a summary for you. Bing will highlight particular phrases and cite where it got that information from, allowing you to verify the claim.

Google is expected to respond in kind. The leading search engine company is seeking to reassure investors about its progress with the powerful LaMDA AI. “Bard” uses a smaller version of LaMDA, and is based on similar technology to ChatGPT. Also, Google has announced its investment in Anthropics – a startup initiated by eleven former OpenAI employees. That company is developing a large language model generative AI system named “Claude” which describes itself “I am an AI-based conversational assistant powered by advanced natural language processing… My goal is to be helpful, harmless, and honest.” Google CEO Sundar Pichai told investors earlier this month that it is planning to roll out its LaMDA language model with search components “very soon.” Imagine the potential of micro-learning and mentoring that will be afforded by these competing search engine chatbots with advanced communication capabilities.

The competition extends far beyond search engines. There are greatly enhanced image generators with improvements compared to DALL-E-2. Muse is one. That is the new Google Text-To-Image Generation via Masked Generative Transformer that can produce photos of a high quality comparable to those produced by rival models like the DALL-E 2 and Imagen at a rate that is far faster. Imagine having your own personal artist at your fingertips to create images and graphics at your command.

While at the moment ChatGPT can’t generate music from text prompts, Google is describing a new, experimental AI model, MusicLM, which can create a song from a simple text input. The new AI model can make anywhere from a 10-second audio clip to a full song, using as many specific details as you give it. It can also modify an existing song and produce a different rendition. Some rather interesting demo examples from Google are shared here. Imagine the impact on higher education music departments, garage bands, music services, and courses.

ChatGPT can already write and debug code well enough to get a job at Amazon. It learned this skill from GitHub, but soon it is scheduled to take lessons from actual engineers. OpenAI is hiring 1,000 coders, in part to explain their methods to ChatGPT in natural language. You might consider this a kind of continuing education for ChatGPT. Imagine having your own personal coder to write new apps and personalize existing products to your personal preferences.

One important aspect of the emergence of generative AI that has not received enough attention for those of us in higher education is that the output of these systems is not subject to copyright. Lumen Learning co-founder, David Wiley, writes in his blog, opencontent.org:

Because copyright law as codified in the 1976 Act requires human authorship, the Work cannot be registered…. as the US Copyright Office is concerned, output from programs like ChatGPT or Stable Diffusion are not eligible for copyright protection…. unless something rather dramatic happens along these lines, the outputs of generative AI programs will continue to pass immediately into the public domain. Consequently, they will be open educational resources under the common definition.

With the upgrades expected out in coming weeks, we can look for access to even more up-to-date information than the current version of ChatGPT – it will grow with the Web. We can expect even faster responses with audio, graphics and video. And, all of these are open. Imagine what that means for ownership of academic materials and OER.

As Chandra Steele writes in PC magazine, “It’s certainly getting ready to enter quite a few professions. ChatGPT is learning to pick stocks like Warren Buffett does. It has passed a Wharton Business School exam and a law school exam. It almost argued a case in traffic court in California, but several bar associations shut that down—for now.” Many careers will be touched by generative AI, only a few of which are writers, programmers, accountants, teachers, researchers, and almost any occupation in which research, logic, computation and communication are key skills.

So, what does this mean for our careers, our futures? In the coming weeks, I encourage us all to:

• Diligently follow the development of generative AI skills and abilities so we can become expert in applying them to our work
• Engage with AI so that we develop a personal facility with using the tools as they emerge and develop.
• Continuously grow our own personal, uniquely human, capabilities such as our ethos, empathy, care, and insight into our fellow humans. These will continue to set us apart from AI, for a while.
• Embrace, rather than fear, the technology, applying it to advance the human condition.

We should share this message with our learners as well. As mentors of those entering careers, changing careers, and inventing their own careers in this rapidly changing environment, it is incumbent on us to reinforce the timeless human qualities of insight, compassion and care for each other. These will continue to set us aside and above the artificial.

 

This article was originally published in Inside Higher Ed’s Transforming Teaching & Learning blog.