Artificial Intelligence and the Importance of Overcoming Bias
Artificial intelligence has become one of the most discussed technologies in the modern business and legal landscape. For some, AI represents a transformative tool capable of dramatically improving productivity and changing the way professional services are delivered. For others, it raises serious concerns involving accuracy, confidentiality, ethics, judgment, and overreliance on technology.
Both perspectives contain elements of truth. Both can also become distorted by bias.
In my own experience, I have encountered bias at both ends of the spectrum.
Some professionals are reluctant to adopt AI at all, often citing legitimate concerns such as client confidentiality, hallucinations, data security, and the risk of inaccurate or unreliable output. Those concerns are real and should not be dismissed. However, there are solutions to these concerns. Burying one’s head in the sand is not a strategy.
At the same time, I have also encountered sweeping claims from those promoting AI products that are difficult to reconcile with the realities of sophisticated legal work. For example, claims that artificial intelligence can reduce complex patent drafting to a matter of “only a few hours” may grab the reader’s attention, but they are not consistent with my experience. I have spent a substantial amount of time evaluating artificial intelligence tools specifically tailored for patent practice and found that, while the output of these tools is superficially impressive, it does not approach the quality and depth that an experienced practitioner can generate in say, 25 hours or more. Moreover, the output cannot simply be edited in “only a few hours” to reach this level of quality.
The challenge, therefore, is not simply deciding whether AI is “good” or “bad.” The more important challenge is learning how to evaluate the technology objectively.
Avoiding Reflexive Resistance
Professionals are often skeptical of new technologies, and that skepticism can be healthy. Lawyers, in particular, have obligations that make caution appropriate. Client confidentiality, professional judgment, accuracy, and ethical responsibility are not optional considerations. Any technology used in legal practice must be evaluated through that lens.
But caution can become resistance when concerns are used as a reason to avoid meaningful evaluation altogether.
The fact that AI tools can hallucinate does not mean they have no value. The fact that confidential information must be protected does not mean AI cannot be used in responsible, controlled, and privacy-conscious ways. The fact that AI cannot replace legal judgment does not mean it cannot assist with research, organization, drafting support, issue spotting, review, or administrative efficiency.
Rejecting AI because it is imperfect risks overlooking areas where the technology may provide meaningful value when used appropriately.
Avoiding Uncritical Enthusiasm
The opposite bias can be equally problematic.
AI is powerful, but it is not magic. It can generate text quickly, summarize information, identify patterns, and assist with certain workflow tasks. But speed is not the same as quality. A draft that appears polished on the surface may still contain gaps in reasoning, factual inaccuracies, poor assumptions, or language that fails to reflect the client’s objectives.
This is especially true in areas requiring technical understanding, legal strategy, and professional judgment.
In patent practice, for example, drafting a strong application is not merely an exercise in generating words. It requires understanding the invention, identifying what is technically significant, appreciating the commercial context, anticipating potential prior art, developing claim strategy, and preparing a disclosure that supports meaningful protection. Artificial intelligence may assist with parts of that process, but it does not eliminate the need for careful attorney judgment.
Overstating what AI can do risks creating unrealistic expectations and undervaluing the expertise required to produce high-quality legal work.
A More Objective Approach
The better approach is to evaluate AI neither defensively nor blindly, but deliberately.
That means asking practical questions:
What specific task is the technology being used for?
What are the risks associated with that task?
What information is being provided to the system?
How will the output be reviewed?
Does the tool improve efficiency, quality, or consistency?
Where does human judgment remain essential?
In my view, the most productive use of AI in legal practice is not as a substitute for professional judgment, but as a tool that can support and enhance certain parts of a disciplined workflow. AI may be useful for organizing information, generating preliminary drafts, identifying inconsistencies, improving clarity, summarizing materials, or stress-testing ideas. But the value of those uses depends heavily on the judgment of the person directing and reviewing the work.
Technology Should Serve Judgment
The goal should not be to adopt AI for its own sake. Nor should the goal be to resist it simply because it is new.
The goal should be to understand where the technology can responsibly add value and where it falls short.
That requires setting aside both fear-based resistance and marketing-driven hype. It requires testing tools carefully, evaluating results honestly, protecting client interests, and maintaining professional responsibility at every stage.
Artificial intelligence will almost certainly continue to influence the delivery of legal services. The firms that provide the greatest value to clients will not necessarily be those that use AI the most, or those that avoid it entirely. They will be the firms that use modern technology thoughtfully, ethically, and strategically—while preserving the judgment, care, and accountability that sophisticated legal work requires.
In that respect, AI is best understood not as a replacement for legal expertise, but as another tool whose value depends on the skill, discipline, and integrity of the person using it.
