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When announcing the much publicized $125 million fine against JP Morgan for violating recordkeeping rules, the U.S. Securities and Exchange Commission (SEC) Chair stated that financial institutions did not act as if they got the message regarding unauthorized or unwatched written communications.[1] The Commodity Futures Trading Commission (CFTC) has also fined banks and brokerages billions of dollars for not saving communications.[2] For a long time, businesses had to worry about saving their own authorized communications, but more recently, the SEC has discovered that employees are purposefully discussing business on separate communications channels to avoid company eyes.[3]

As the fines become stiffer for current authorized and unauthorized messaging platforms, the race to develop artificial intelligence, including an AI-powered chatbox, is in full swing.[4] Early tests of AI chat tools show that AI can produce some offensive and crazy responses as they ingest a vast amount of text from the internet.[5] What will federal regulators make of these messages? It is even predicted that workers in the finance industry could be replaced by AI in the areas of financial advising, trading, accounting, and investment banking.[6] In announcing the fine against JP Morgan, SEC Chair Gary Gensler stated: As technology changes, its even more important that registrants ensure that their communications are appropriately recorded and are not conducted outside of official channels in order to avoid market oversight.[7]

Much has been said about the Department of Justices announced changes to its criminal enforcement policies.[8] Kenneth A. Polite, Jr., the Assistant Attorney General of the Criminal Division, emphasized that business-related electronic data and communications must be preserved, and accessible or negative consequences will flow. This includes communications on personal devices, communication platforms, or third-party messaging applications. AI generated messages or information will most likely also be considered business-related electronic data. It is unclear how erroneous or false information from AI will be viewed. But one thing is for sure, the SEC and other agencies will continue to investigate financial firms and whether they have gotten the message or not. Regulated firms need to invest time and resources in developing communications and retention policies now with an eye towards the future of AI.

[1] SEC will reward cooperation where firms mess up with unauthorized communication, Resources, Jennie Clarke, November 17, 2022, http://www.globalrelay.com/sec-will-reward-cooperation-where-firms-mess-up-with-unauthorized-communications.

[2] 16 Wall Street firms fined $1.8B for using private text apps, lying about it, Computer World, Lucas Mearlan, September 28, 2022, http://www.computerworld.com/article/3675289/16-wall-street-firms-fined-18b-for-using-private-text-apps-lying-about-it.

[3] Id.

[4] Microsofts new AI chatbox has been saying some crazy and unhinged things, NPR, Bobby Allyn, March 2, 2023, http://www.npr.org/2023/03/02/1159895892/ai-microsoft-bing-chatbox.

[5] Id.

[6] ChatGPT may be coming for our jobs. Here are the 10 roles that AI is most likely to replace, Business Insider, Aaron Mok and Jacob Zinkula, April 9, 2023, http://www.businessinsider.com/chatgpt-jobs-at-risk-replacement-artificial-intelligence-ai-labor-trends-2023-02.

[7] JPMorgan Admits to Widespread Recordkeeping Failures and Agrees to Pay $125 Million Penalty to Resolve SEC Charges, U.S. Securities and Exchange Commission Press Release 2021-262, December 17, 2021, http://www.sec.gov/news/press-release/2021-262.

[8] DOJ Takes Stance on Messaging Apps, Details Comp Reforms, Law 360, Stewart Bishop, March 3, 2023, http://www.law360.com/articles/1582115/doj-takes-stance-on-messaging-apps-details-comp-reforms.

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What is the Message from Artificial Intelligence | Butler Snow LLP ... - JD Supra

WEST LAFAYETTE, Ind. A technology with the potential to transform all aspects of everyday life is shaping the next pursuit at Purdue University. With the programs, research and expertise highlighted below, Purdue is guiding the advancement of artificial intelligence. If you have any questions about Purdues work in AI or would like to speak to a Purdue expert, contact Brian Huchel, bhuchel@purdue.edu.

AI presents both unique opportunities and unique challenges. How can we use this technology as a tool? Researcher Javier Gomez-Lavin, assistant professor in the Department of Philosophy, shares the work that needs to be done in habits, rules and regulations surrounding those who work with AI.

Hear researcher Aniket Bera explain more about his groundbreaking work to bring human behavior into AI and what sparked his interest in the technology. In this interview, Bera touches on the importance of technology in human emotion and the goal of his research lab.

Is AI trustworthy? Hear Purdue University in Indianapolis researcher Arjan Durresi explain how making AI safe and easy to understand for the everyday user requires treating the development of the technology like the development of a child.

AI is touching almost every subject, discipline and career field as it evolves. In human resources, the technology has already been used as a selection tool in job interviews. Professor Sang Eun Woo explains how we can turn this use of AI as a selection tool into a professional development tool.

How will AI influence writing and education? Harry Denny, professor of English and director of Purdues On-Campus Writing Lab, answers how ChatGPT and other AI programs may be integrated into the classroom experience.

The rise of ChatGPT has created concerns over security. Professor Saurabh Bagchi shares the reality of cybersecurity concerns and how this technology could be used to strengthen the security of our computing systems.

How Purdue is helping design artificial intelligence, raise trust in it

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Purdue University professor working to help robots better work with humans

WGN-TV Chicago

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Approaching artificial intelligence: How Purdue is leading the ... - Purdue University

If you have people making decisions from data, you probably need artificial intelligence but not the kind that's making headlines right now.

The sensational headlines this week are about generative chatbots programs like ChatGPT that carry on natural-sounding conversations in (written) English. They're amazingly lifelike and seem to be thinking for themselves.But the things they say are often false, and even when telling the truth, they can't tell you where they got their information.They're working from large tables of how words are commonly used, not information about the outside world. So despite the "wow" factor, they're not, by themselves, the right tool for anything in mortgage lending that I can see.

Chatbots do have their uses. You might want to have a web page that takes customers' questions in plain English and answers them. Generative technology can be useful on the input side, for recognizing different ways of wording a question, but the answers have to be controlled. When a customer asks for his loan balance, the chatbot must actually look up the balance, not just make up something that uses words in a plausible way. Even if the computer misunderstands the question, it must not spout falsehoods.

But chatbots are just one tiny part of AI.They are one application of machine learning, which itself is still not the whole of AI, but let's look at that next.

Machine learning means getting software to recognize patterns and train itself from data.Machine learning is very useful for finding statistical regularities and estimating probabilities. It is basically statistical regression, greatly expanded into many dimensions.Neural networks are one kind of machine learning, and they are multi-layer statistical models, not models of brains.

The results of machine learning are only probable, not certain.You have to be ready to live with inaccuracy.Fortunately, people recognize that the answers aren't coming from a conscious human mind, and it's easier for humans to be cautious.Machine learning will tell you whether a borrower is probably a good risk. It will not tell you for certain exactly what that borrower will do.That is easy to understand, and useful.

Apart from inaccuracy, the big risk with machine learning is that it will learn the wrong things specifically, discriminatory decisioning. If you tell a computer to find patterns, it will find them, whether or not they are patterns society wants to perpetuate. If the data used to train a machine learning model reflects historic racial bias, it may discover this and perpetuate it in its predictions. It has no way to know you don't want it to use that knowledge. It might even detect race indirectly, from location (old-fashioned illegal redlining), or choice of hairdressers, or anything else.

How strongly you guard against this depends on what you are using machine learning for. If you're just plotting an advertising strategy or making predictions internally, the prejudiced computer may not violate laws or regulations but if it's making decisions about people, it certainly will. The cure is to block inappropriate information from being used, so the machine is only learning from data you're entitled to use, and also to test the results to see if the system is in fact biased.You usually cannot look at the machine learning system to find out what it learned, because the patterns are hidden in matrices of numbers.

But even that isn't all of AI.Traditionally, AI comprises all uses of computers that are based on the study of human thought.That includes some technologies that are not in today's limelight but are very applicable to finance.They revolve around knowledge-based systems and explicit rules for reasoning.

One time-honored method is knowledge engineering: Get a human expert, such as a loan underwriter, to work through a lot of examples and tell you how to analyze them. Then write a computer program that does the same thing, and refine it, with help both from the human expert and from statistical tests. The result is likely to be a rule-based, knowledge-based system, using well-established techniques to reason from explicit knowledge. And it can well be more accurate and reliable than the human expert because it never forgets anything.On the other hand, unlike the human expert, it knows nothing that was not built into it.

Knowledge engineering mixes well with machine learning approaches that output understandable rules, such as decision trees. There are also ways to probe a machine learning system to extract explicit knowledge from it; this is called explainable AI (XAI).

Of course, knowledge-based systems face a pitfall of their own that we recognized long ago: "As soon as it works reliably, it's no longer called AI!" But we're in business to make good decisions, not to impress people with magic.

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What is safe artificial intelligence in mortgage lending? - National Mortgage News

Avid Disney vacation planners know that using technology to help plan a Disney vacation is as old as tech itself. When the internet still had that new car smell, us Disney planners flocked to Disneys fledgling website and independent chat groups to help craft magical vacations.

Many decades later, we still utilize online resources and discussion boards, like DISboards, but today we have social media, vlogs, podcasts, and even TikToks. This brings me to the new kid on the planning block Artificial Intelligence.

Chat GPT is an online platform that allows almost anyone with an internet connection to have a chat dialogue with an artificial intelligence bot. But, lets let ChatGPT answer the question.

You will find pros and cons of utilizing artificial intelligence like ChatGPT. So I thought, why not begin my AI adventure exploring a subject with which I am extremely familiar: Disney Cruise Line.

Below you will see screenshots of questions I have asked, along with the answers generated by Chat GPT.

If you can use a search engine, you can use Chat GPT. I simply asked, What is Rotational Dining on Disney Cruise Line? and this is the answer provided.

I also asked, What Port Adventures are available on Disneys Castaway Cay?

So far, so good, but these are fairly simple questions.

ChatGPT provides users with answers that are conversational and authoritative meaning it really thinks it knows what it is talking about. However, if you ask ChatGPT, it will sometimes admit the answers provided are simply wrong.

For example, I asked ChatGPT How much should I tip on Disney Cruise Line? and this is the response given.

Current gratuities charged are $14.50 per guest per day. Also, bar, beverage, and spa services gratuities are actually 18%, not 15%. It is a small detail, but one you wouldnt catch unless you had previously sailed with Disney Cruise Line or had already done your research.

ChatGPT does offer a feedback option. You can utilize the Thumbs Up or Thumbs Down icons at the top of your answer, or you can provide the correct information in the chat field. That does not mean the answer will be corrected the next time you ask. It only means that the artificial intelligence will group your response with the information it has already gathered from various sources.

For me, the best feature of ChatGPT is that I can ask the program a question as if I was talking with a person. You can ask for ideas like:

This AI is aware that it has limitations. For vacation planners, this tool can help spark ideas on what activities are available at destinations worldwide. However, it cannot provide real-time travel information, nor can it give you travel quotes or help you book travel.

That last suggestion about contacting a travel agent is good advice. Lets see what ChatGPT has to say about that.

Visit the human agents over at Dreams Unlimited Travel the official sponsor of DCL Fan to request your free, no-obligation quote from one of our experienced Disney Cruise Line travel planners who will be happy to assist you when planning a Disney Cruise Line vacation for the humans in your traveling party.

Melanie is the mom of three young adults. She is a native Floridian who now lives in North Carolina. She is a Gold Castaway Club Member who has sailed on all four of the current ships at least once and is ready to set sail on the Disney Wish this fall.

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Using an Artificial Intelligence Interface to Plan a Disney Cruise - DCL Fan

What GAO Found

Artificial intelligence (AI) is evolving at a rapid pace and the federal government cannot afford to be reactive to its complexities, risks, and societal consequences. Federal guidance has focused on ensuring AI is responsible, equitable, traceable, reliable, and governable. Third-party assessments and audits are important to achieving these goals. However, a critical mass of workforce expertise is needed to enable federal agencies to accelerate the delivery and adoption of AI.

Participants in an October 2021 roundtable convened by GAO discussed agencies' needs for digital services staff, the types of work that a more technical workforce could execute in areas such as artificial intelligence, and challenges associated with current hiring methods. They noted such staff would require a variety of digital and government-related skills. Participants also discussed challenges associated with existing policies, infrastructure, laws, and regulations that may hinder agency recruitment and retention of digital services staff.

During a September 2020 Comptroller General Forum on AI, experts discussed approaches to ensure federal workers have the skills and expertise needed for AI implementation. Experts also discussed how principles and frameworks on the use of AI can be operationalized into practices for managers and supervisors of these systems, as well as third-party assessors. Following the forum, GAO developed an AI Accountability Framework of key practices to help ensure responsible AI use by federal agencies and other entities involved in AI systems. The Framework is organized around four complementary principles: governance, data, performance, and monitoring.

Artificial Intelligence (AI) Accountability Framework

To help managers ensure accountability and the responsible use of AI in government programs and processes, GAO has developed an AI Accountability Framework. Separately, GAO has identified mission-critical gaps in federal workforce skills and expertise in science and technology as high-risk areas since 2001.

This testimony summarizes two related reportsGAO-22-105388 and GAO-21-519SP. The first report addresses the digital skills needed to modernize the federal government. The second report describes discussions by experts on the types of risks and challenges in applying AI systems in the public sector.

To develop the June 2021 AI Framework, GAO convened a Comptroller General Forum in September 2020 with AI experts from across the federal government, industry, and nonprofit sectors. The Framework was informed by an extensive literature review, and the key practices were independently validated by program officials and subject matter experts.

For the November 2021 report on digital workforce skills, GAO convened a roundtable discussion in October 2021 comprised of chief technology officers, chief data officers, and chief information officers, among others. Participants discussed ways to develop a dedicated talent pool to help meet the federal government's needs for digital expertise.

For more information, contact Taka Ariga at (202) 512-6888 or arigat@gao.gov.

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Artificial Intelligence: Key Practices to Help Ensure Accountability in ... - Government Accountability Office