A.I. is playing many roles in many sectors. One of the emerging uses for A.I. is using natural-language processing (N.L.P.) to analyze communications for potential compliance problems.
The Five Most-Key Takeaways from This Blog Post
- One example of this is in finance, where terminology and slang can make it hard for an outsider to detect whether something like insider trading is going on. Wall Street Journal published a write-up about how A.I. can learn the lingo, so to speak, to detect in messages whether anything fishy is going on.
- Machine translation is also a perk of A.I., as a single A.I. tool could be adept at translating over 100 languages in analyzing communications for compliance. This could be especially useful for multinational corporations (M.N.C.’s).
- For business owners, these tools could make it much easier to monitor employee communications through company accounts.
- This application of A.I. connects to the larger trend of developing A.I. tools that function like subject-matter experts. Since A.I. can analyze a ton of data, giving it a wealth of data about, say, the regulations of the finance industry can allow it to make informed predictions about whether a regulation is being followed or not.
- Challenges still exist, however. Encrypted, anonymous-ish communication channels indeed do exist. Plus, there is always the meet-in-a-dark-parking-garage offline communications that could go on.
The Challenge of Workarounds
To leap straight from the fifth bullet point into the main text of this blog, the significance here is that A.I. will not be able to catch all regulatory infractions.
More likely, it will catch the regulatory infractions that get discussed on traditional online communication channels, such as emails or communications app (Meta Messenger, for instance).
For this reason, then, businesses can relax knowing that A.I. can catch some of the easier-to-catch, sloppier slip-ups by regulation-breakers.
This, on the other hand, can allow compliance staffers to focus on those harder-to-pursue cases.
For smaller businesses without a compliance staff, then this A.I. can at least afford a peace of mind that some infractions could indeed be caught that would otherwise go unheeded.
That being said, the problem of false positives because of A.I.’s issues with common sense can be a potential problem. Read on below for more insight into this issue.
The Connotation Conundrum
Something that A.I. will need to prove itself in as these tools become better is whether A.I. can adapt to some of the trickier uses of language.
For instance, suppose two employees have a humorous rapport that they maintain on messaging apps.
Much of the time, they use irony, with a running joke wherein they blatantly conspire (jokingly, remember) to break a regulation.
To an A.I. tool, would it be clear that these two employees are just kidding around, or would this get flagged as an obvious infraction?
This alone presents an argument for not fully automating compliance, as a human compliance staffer who has a common-sense grasp of irony will be able to quickly clear things up.
Whereas, A.I. that immediately notifies higher-ups and even regulatory agencies could cause a lot of time-consuming headaches for people whose time would be better spent hunting actual infractions.
The Last (But Not Least) Key Takeaway from This Blog Post
Compliance in any industry can be hard to oversee, no matter the size of the business. Whether through malice or mere ignorance, a compliance infraction can be an expensive mistake for a business.
A.I. can help detect infractions before they occur. Or, if someone is already crossing the line, A.I. can give companies a better chance at nipping the problem in the bud before it grows into a large, expensive issue for the company to deal with.
Other Great GO AI Blog Posts
GO AI the blog offers a combination of information about, analysis of, and editorializing on A.I. technologies of interest to business owners, with especial focus on the impact this tech will have on commerce as a whole.
On a usual week, there are multiple GO AI blog posts going out. Here are some notable recent articles:
- For Businesses and Other Organizations, What Makes a Successful Chatbot?
- IBM Watson vs. ChatGPT vs. Gemini: How Will Each Affect Search Engines?
- Using A.I. to Find Resources for Business Owners
- How Would Restricting Open-Source A.I. Affect Business Owners?
- The EU’s A.I. Act Has Become Law: The Implications for Business Owners (Especially American)
In addition to our GO AI blog, we also have a blog that offers important updates in the world of search engine optimization (SEO), with blog posts like “Google Ends Its Plan to End Third-Party Cookies”.
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