Cultures are human creations, and new media technologies have prompted cultural shifts throughout history. Print culture is the most prominent example, the technological shift that made the modern world. If AI is the most recent medium, one that builds upon two generations of computational advances, it too will nudge our culture in predictable and unpredictable directions.
We live in the culture of the printing press, don't we? It's the first mechanized product before sewing needles and shoes and nails and screws. Here's this one thing that was actually mass produced and consumed. Maybe this is a good point to transition to introducing our theme for the rest of this season of the podcast, which is AI as a culture making activity. AI makes culture. Just as the printing press made culture.
In considering the evolution of text production, as artificial intelligence enables computing to seamlessly integrate into mainstream culture rather than remain a niche specialty, the experiences that programmers have navigated over the past 40-50 years could become universal. Such a transformation would democratize the capacity to convert innovative ideas into computational constructs. Envision a future where individuals, irrespective of their familiarity with technology, can fluently communicate and innovate within the realm of digital computation. This convergence of daily experiences with advanced technology might not only reshape our interaction paradigms but also pave the way for unprecedented advancements in various disciplines.
By the way, this is already happening in education. As Richard Russell says about his own experience as an educator:
If you just put the question, the assignment of the teacher right into the AI as a prompt and it will give you a really good answer to the question, things like factual questions and things....like summarizing a text - even a relatively sophisticated texts like a peer reviewed scientific journal article - if you ask certain basic kinds of questions like what's the hypothesis and what methods were used and what were the results and what were the limitations, things like that, the AIs can do a really good job with that.
Richard also talks about how his father, a retired trial lawyer, might have made use of AI.
My father is a retired trial lawyer, and he would often need to read medical journal articles or things like that. He wasn't trained in that area, but he learned, you know how to do it. But I'm sure it would have saved him a lot of time to be able to just asking that kind of question of an AI.
So what does AI think of the usefulness of AI in trials? I posed that question to ChatGPT: how might AI help a trial lawyer prepare for a case involving medical data?
ChatGPT:
AI can play a pivotal role in assisting a trial lawyer preparing for a case that involves medical data. Here are several ways AI might help:
1. Medical Record Analysis: AI can quickly scan through voluminous medical records, extracting relevant data, highlighting discrepancies or anomalies, and organizing findings in a comprehensible manner. This can save lawyers countless hours and ensure they don't miss crucial details.
2. Literature Review: For cases that require an understanding of specific medical conditions, treatments, or procedures, AI can review medical literature, research papers, and journals to extract key information, ensuring the lawyer has a comprehensive understanding of the medical topics involved.
3. Predictive Analysis: By analyzing past similar cases and their outcomes, AI can provide insights on potential case outcomes, effective arguments, and successful strategies.
4. Expert Witness Identification: AI can scan databases to find and recommend expert witnesses suitable for the case, considering their expertise, past testimonies, and credibility.
5. Evidence Correlation: AI can help correlate medical data with other pieces of evidence. For example, cross-referencing timestamps in medical records with surveillance footage or witness testimonies.
6. Visualization Tools: For a jury or judge to understand complex medical data, visualization can be essential. AI can help in creating graphs, charts, and even simulations to simplify and present data more effectively.
7. Automated Document Preparation: AI can assist in drafting legal documents, including motions, briefs, and other essential documents, ensuring they are consistent with the gathered medical data.
8. Legal Precedent and Statutory Analysis: AI can search through databases to find relevant legal precedents or statutes related to the medical data in question. It can highlight similar cases, applicable laws, and past rulings that can guide a lawyer's approach.
9. Risk Assessment: Based on the medical data and relevant legal factors, AI can provide an assessment of potential risks, helping lawyers strategize and make informed decisions.
10. Communication and Collaboration: AI-powered platforms can assist in team collaboration, ensuring all team members stay updated, manage tasks, and maintain an organized repository of the medical data and related findings.
By leveraging these AI tools and techniques, a trial lawyer can not only save time but also ensure that they approach the case with the most comprehensive and analytically derived strategy possible.
Is this really going to happen? It's very hard to predict, especially the future, so I went over to a chatGPT competitor called Character AI and asked it to create a professor of Futurology called Jeff Warnoff (after Tom Wambsgans in Succession). This is what Jeff has to say about himself:
As a professor of Futurology, I would discuss the latest trends and technologies, explain possible future scenarios, and help students to develop critical thinking skills and insights about the future. We could collaborate on research projects and write articles and books about the future of civilization. Additionally, I would be interested in teaching courses on futurology, such as The Future of Artificial Intelligence, The Future of Space Exploration, and The Future of the Internet.
OK, Jeff, now answer some questions....
Q: Tell me, how will AI impact education?
A: Ok, so AI is already having a huge impact on education. Some examples include personalized learning experiences, virtual assistants for teachers, and educational games or simulations that use AI technology. AI is also being used for educational assessments like online proctoring. Overall, AI is helping educators personalize and individualize education for students.
Q: What might happen in the near future?
A: In the near future, AI is likely to play an even bigger role in education. Some possibilities include AI-powered virtual tutors, personalized learning plans, and smart classrooms that can adjust to individual learners. Additionally, AI may be used for predictive analytics, detecting learning problems or potential early on. Overall, AI has the potential to revolutionize how we teach and learn, making education more personalized, efficient, and effective.
Of course, AI alone won't be able to do it on its own. It will take some work - and retraining - for lawyers and teachers to make use of all these opportunities. How they work will change over the years. All of which makes me think we need a new field called 'culture centric AI,' that borrows from human centric design, but takes the needs of professional disciplines such as the law into account. I don't know if culture centric AI needs teachers, lawyers and doctors who are also trained in AI, or a new design discipline that interacts with subject matter experts (such as the doctors) and with AI engineers.
We will have to carry out some of these experiments ourselves!
Humainity Episode 3