Unpacking ChatGPT for the Information Management Industry
Take a deep breath. This is another article about ChatGPT and Generative AI.
I'll be honest. I am the type of person that struggles to resist a good hype cycle. In 2021, I couldn't stop talking about the metaverse. I even organized a half-day workshop on the metaverse, with part of the event held in the metaverse. It was very meta.
I have learned to temper my enthusiasm with analysis, though. With any innovation or technology, here’s how I respond:
Seek understanding. How does the new technology work? What is the business model, and how is the company earning revenue? What is the product's competitive advantage?
Identify use cases. What are the possible applications for this technology in my organization? Map feasibility and impact of use cases. What is the feasibility of implementing each use case based on the maturity of the technology, level of effort, resources, and other priorities? What impact would the use case have on the organization if successful (e.g., revenue increase, cost savings, etc.)?
Develop a strategy that considers the strengths and weaknesses of the new technology as well as the opportunities and threats it presents (i.e., a SWOT analysis). Imagine possible scenarios based on opportunities and threats. Identify the probability and impact of scenarios.
The amount of time you spend on the analysis could vary depending on your level of concern or interest. Here's my first pass at thinking about Generative AI and its impact on the Association for Intelligent Information Management (AIIM) and its members.
Launched as a prototype in November 2022, ChatGPT is a chatbot capable of human-like conversation. It’s built using Open AI's Generative Pre-training Transformer 3 (GPT-3) technology. GPT-3 is one of the largest language processing AI models with 175 billion parameters. OpenAI has a nice explanation of how ChatGPT works and how they’re training the model. BBC Science Focus also has a nice breakdown.
Here's my take. ChatGPT’s value is in its ever-growing data model. Users testing the free model are helping to grow the dataset, which will, in turn, improve the chatbot’s breadth and accuracy.
ChatGPT’s business model is harder to discern. Both Microsoft and Google have invested in generative AI, and it has a clear value proposition for improving the user experience when searching. Will that enhanced user experience be enough to increase search engine usage of Bing or Google, which could increase advertising revenue?
Use Cases, Feasibility, and Impact
I’m going to share one possible use case for AIIM.
Our marketing team could use Generative AI to develop content, a boon in a 24/7 content cycle where you are only as strong as your conversion funnel. This could save us staff time and allow our team to shift attention to quality control, content strategy, and content distribution. From a feasibility standpoint, I don’t think we are there yet. ChatGPT has natural, well-written responses, but there are reported inaccuracies in the output, and ChatGPT struggles with niche content.
ChatGPT is just plain fun. The simple, clear user experience and human-like dialogue sped adoption and made the app go viral.
ChatGPT pulls from a massive and growing dataset.
The output of Generative AI is only as good as the dataset. ChatGPT’s data is at least a year old, so you may get outdated information.
ChatGPT’s depth of knowledge and accuracy is questionable.
ChatGPT doesn’t provide sources for research or data to verify accuracy.
Information management professionals have an opportunity to help their organization understand the impact of ChatGPT and generative AI. IM professionals could be at the forefront of this new technology.
Generative AI will spin up a new ecosystem of hardware and vendor providers seeking to manage the information it generates by ensuring veracity, intellectual property, and compliance. We’ve already seen the development of apps, like GPTZero, designed to identify AI-generated content. Note: ChatGPT can only recognize something it wrote if the words have not been changed. This could be an opportunity for AIIM to expand its community.
Will generative AI present an opportunity for creatives? Will we put a higher value on human-generated content? I could foresee a future where media, artists, and marketing and communication professionals will start to tout human-generated content as superior and will develop an online credentialing or badging system to denote human-generated content. Like the labeling of “organic” goods, this will be a challenging claim to prove and regulate.
Could generative AI make processes more equitable by breaking down complex processes? For example, could ChatGPT be used to make application processes for college admissions, financial aid, or home mortgages simpler by helping consumers navigate a convoluted process?
Generative AI content may increase the volume and velocity of information, and it will certainly test our ability to identify the veracity of content.
There are already reports of students using ChatGPT to plagiarize work, and schools are banning its use.
Outside of an academic setting, it may be important for us to know when content was AI-generated, such as a cover letter or writing samples for an interview process.
Generative AI could make cybercrime easier. The cybersecurity industry will start focusing on how to identify content produced by Generative AI in phishing and social engineering.
Knowledge workers' skill sets may need to transform. I do not believe whole professions will be replaced by generative AI (at least not overnight), but we may need new skill sets. The ability to complete rote, routine tasks will be devalued. Empathy, contextualization, creativity, facilitation, and ethics will be key skill sets going forward. These are the skill sets that distinguish us from the machines and that make us human.
We’re in the Wild West era of generative AI. There will be exciting discoveries and startling scandals ahead. It may take years for generative AI to truly mature. If you think back to the early days of the internet, maturity came with standardization and regulation. When we have norms to govern generative AI, it will be easier to trust it to be a larger part of our professional and personal lives.
About Tori Miller Liu
Tori Miller Liu, CAE, MBA is the President & CEO of the Association for Intelligent Information Management. She is an experienced association executive, technology leader, speaker, and facilitator. Previously, she served as the Chief Information Officer of the American Speech-Language-Hearing Association (ASHA) and has 16+ years of experience in association management. Tori is a member of the ASAE Technology Professional Advisory Council and a founding member and Board Member of Association Women Technology Champions. She was named a 2020 Association Trends Young & Aspiring Professional and 2021 Association Forum Forty under 40 award recipient. She is also an alumna of the ASAE NextGen program. She is a Certified Association Executive and holds an MBA from George Washington University.