Jason Lohr (San Francisco) held the first in a series of internal webinars on the basics and legal implications of artificial intelligence (AI) and machine learning, highlighting their relevance to IPMT.
AI touches nearly every industry and is used to solve complex problems, spot and minimize risks, improve decision-making, and develop new products. Key issues and tips for navigating this complex area were covered, including:
- The current state of AI and key concepts: As AI is still relatively new, the best way to develop a better understanding is to become familiar with the terminology and concepts surrounding AI. Concepts include data classification, inferring information from input data, and identifying objects by comparison with input data-set, machine learning and artificial neural networks (ANN), AI hardware characteristics, and patent filing trends. Further it is important to be able to distinguish between conventional technology, AI, and IoT (the internet of things).
- Practical uses and instances of machine-learning and AI: Insurance risk analysis, service offering based on user behavior, automated legal document drafting—AI can provide these types of services through identifying and recognizing patterns to make informed decisions that can make our lives more efficient and safe.
- Predictions of where AI is going: Examining the current state of AI can predict where it is heading. AI should be able to operate autonomously to communicate, create, and perform as a human would, opening up larger issues about Big Data & IoT.
- AI as a legal tool: AI tools are predicted to affect the legal profession as cloud-based tools become more prevalent among in-house counsel. Law firms can use tools such as Luminance, Nalytics, and Lex Machina to review, analyze, assess, and minimize risks. However AI cannot fully draft a patent or contract, which is why paralegals and associates are still very much needed to conduct the actual legal analysis.
- Concerns: With the excitement around AI comes concerns. Common issues include concerns over data protection, proof of compliance, due diligence, when to patent AI or machine learning, ethical considerations, risks, and non-lawyer assistance.