“We always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next 10.” These wise words from Bill Gates remind us not to let ourselves be “lulled into inaction.” This sentiment rings especially true when considering the transformative potential of artificial intelligence (AI) in the business world.
Just as the advent of personal computers and the internet revolutionized many sectors, including law, AI is poised to do the same. But the changes won’t be as instantaneous as some predict. Today, as part I of this multipart series, we’ll explore AI, and its recent developments.
AI: What Is It?
AI, in its simplest form, is a diverse set of technologies designed to mimic human-like cognitive functions that started coalescing in the early 1950s. It uses various methods to analyze data, predict patterns and adapt to perform tasks more efficiently over time. Machine learning and deep learning – subsets of AI – focus on developing algorithms that learn from and make predictions or decisions based on data sets.
These processes have evolved from supervised learning, where humans label data inputs before processing, to unsupervised learning, where systems learn autonomously without intervention, and now to reinforcement learning, where systems learn by trial and error.
Deep learning employs artificial neural networks to process complex data sets, closely mimicking the human brain’s functionality. According to OpenAI’s CEO, Sam Altman, the AI model for its ChatGBT4 product is made up of an astonishing 100 trillion neural networks.
Despite AI’s long history spanning more than 70 years, it has faced numerous challenges, including the requirement for billions of data elements, limited understanding, interactive capabilities and lack of transparency. However, recent advancements like the Generative Pretrained Transformers (GBT AI) have significantly overcome these hurdles.
GBT AI: The Game Changer
GBT AI models like ChatGBT are pretrained with massive amounts of data, usually harvested from the internet, and then fine-tuned using reinforcement learning. This enables the models to generate responses, which are then filtered through a content moderation module before reaching the recipient. Unlike traditional models, GBT AI continues to improve as it is fed more data, offering a breakthrough in the field of AI.
The substantial improvements in GBT AI over successive versions is a testament to its revolutionary potential. The system learns from incremental changes, refining the data inputs, which collectively have a significant impact. This mirrors Jeff Bezos’ 2017 assertion that AI is a quiet yet meaningful support system that propels substantial operations.
Understanding GBT AI’s Limitations
While GBT AI has made remarkable strides – and captured the recent widespread attention of the media and businesses alike – it is essential to recognize its limitations. These include “hallucinations,” where the system confidently gives an inaccurate, often fictional response, and the lack of real-time adaptability. The model can also potentially perpetuate biases present in its training data, and its decision-making process remains opaque, often referred to as the “black box” problem. These limitations mirror philosopher Michael Polyani’s “Polyani’s Paradox” in humans, where we know more than we can explain.
Ethical and Legal Considerations
While AI has the potential to transform various industries and businesses significantly, it is vital to approach its deployment with both ethical and legal considerations in mind. Given the inherent limitations and possible biases within AI technologies, it’s essential to apply them judiciously across different business sectors, with a careful eye kept on risk management.
The use and application of AI, and GBT AI especially, must include maintaining human oversight and adhering to ethical standards to ensure fairness, transparency and compliance with laws and regulations. For example, in the human resources area, New York City recently enacted a law that requires companies that use an automated employment decision tool to perform bias audits within one year of the tool’s use, make information about the bias audit publicly available, and notify employees and job candidates that the company is using such tools to evaluate them. (read more about AI’s impact on HR on our humanresourceslawblog.com)
Federal agencies are also starting to pay close attention to AI and its impact on businesses, consumers and the workplace. In April 2023, officials from the Justice Department’s Civil Rights Division, Consumer Financial Protection Bureau, Equal Employment Opportunity Commission, and Federal Trade Commission jointly committed to enforcing laws and regulations applicable to their agencies as they relate to AI. As AI becomes increasingly prevalent in day-to-day life, the agencies pledged to “vigorously use [their] collective authorities to protect individuals’ rights regardless of whether legal violations occur through traditional means or advanced technologies.”
AI: The New Frontier and its Impact in Business
AI’s development and application to business is a fluid and ever-evolving area, paralleling the dynamic nature of modern business itself. Recent successes, such as AI algorithms achieving remarkable benchmarks in various tasks, attest to the technological strides made in this area.
However, it is important to note that these advancements must not overshadow the importance of ethical considerations and regulatory guidelines surrounding AI’s application – many of which are yet to come.
As we continue to observe the ongoing evolution of AI, we may reflect on the need for proactive engagement and foresight: Let’s not be lulled into inaction, but rather stay ahead of the curve, preparing for the changes that are yet to come. With preparedness, vigilance and an unwavering commitment to ethical principles, individuals and business owners can harness the power of AI to revolutionize business practices and create new opportunities for innovation and growth.