Finance Transforming insurance with generative AI

The client might have already been lulled into assuming that the generative AI always tells the absolute truth. It is a recipe for endangerment, see my coverage at the link here. TR-1b is the second subtype and consists of the client using generative AI as part of the therapeutic process. In this use case, the therapist is not making use of generative AI, only the client is doing so.

You can now use that spreadsheet as your career planning guide for prompt engineering purposes. Keep it updated as you proceed along in your adventure as a prompt engineer who wants to do the best that you can. The use of purposefully vague prompts can be advantageous for spurring open-ended responses that might land on something new or especially interesting. For various examples and further detailed indications about the nature and use of vagueness while prompting, see my coverage at the link here.

Worse still, they can allow themselves and others to get into dire situations because of an assumption that the AI will be sentient or human-like in being able to take action. That’s why there has been an uproar about students being able to cheat when writing essays outside of the classroom. A teacher cannot merely take the essay that deceitful students assert is their own writing and seek to find out whether it was copied from some other online source. Overall, there won’t be any definitive preexisting essay online that fits the AI-generated essay.

• If the matter is serious, please take it seriously.
• Maybe you’ve been addicted and know first-hand what that’s like.
• Rather than doing an introspective examination that they opted to toss asunder prompt engineering, they will likely bemoan that generative AI is confusing, confounding, and ought to be avoided.
• This is being done in a sense voluntarily by the AI makers and there aren’t any across-the-board laws per se that stipulate they must enact such a restriction (for the latest on AI laws, see my coverage at the link here).

Some have pointed out that this undercuts a sense of transparency about the AI app. A somewhat smarmy remark is that for a company that is called OpenAI, their AI is actually closed to public access and not available as open source. You might find of interest that ChatGPT is based on a version of a predecessor AI app known as GPT-3. ChatGPT is considered to be a slightly next step, referred to as GPT-3.5.

From Frankenstein to Wall-E, humans have long grappled with fears of the effects of technology. Over the course of the next three years, there will be many promising use cases for generative AI. The most valuable and viable are personalized marketing campaigns, employee-facing chatbots, claims prevention, claims automation, product development, fraud detection, and customer-facing chatbots. Although there are many positive use cases, generative AI is not currently suitable for underwriting and compliance. AI is also facilitating the development of new types of insurance such as parametric insurance and on-demand insurance.

For example, AI-powered chatbots can help customers file claims as well as answering questions about the claims process. In some cases, perhaps where they have had an accident that was their fault, people prefer talking to a machine rather than a human who they feel might be critical. For this to work effectively, customers must know when they are talking to a machine and have the option of moving to a human when they wish. In a sense, you trick, dupe, hoodwink, or otherwise bamboozle the AI into giving you an answer. I’ll indicate next what each one of those consists of. The setting up of your own instance was earlier covered herein.

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This is a common topic and a top-of-mind issue confronting modern-day society. Maybe you’ve been addicted and know first-hand what that’s like. For my ongoing readers and new readers, this hearty discussion continues my in-depth series about the impact of generative AI in the health and medical realm. The focus this time is once again on the mental health domain and examines the addictive use of generative AI.

If you provide a prompt that is poorly composed, the odds are that the generative AI will wander all over the map and you won’t get anything demonstrative related to your inquiry. Okay, now then, if you are desirous of being an all-out prompt engineer, the best of the best, the top banana, here’s my lay-down-the-gauntlet challenge for you. However, there are major roadblocks to faster AI adoption due to advisors not having the time or resources to learn the tools. They also don’t always know which tools are best for their practices. Well, yes and no, in the sense that there are tradeoffs involved in doing so. Addiction has a lot of complexities and the idea of just summarily dropping the addiction overnight is not necessarily the most suitable ploy.

It is anticipated that GPT-4 will likely be released in the Spring of 2023. Presumably, GPT-4 is going to be an impressive step forward in terms of being able to produce seemingly even more fluent essays, going deeper, and being an awe-inspiring marvel as to the compositions that it can produce. The news about the AI app goes through the roof and gets widespread attention. People in these companies that have all these cybersecurity protections opt to hop onto a generative AI app. Wham, they have now potentially exposed information that should not have been disclosed. Overall, a bit of irony comes into the rising phenomena of employees willy-nilly entering confidential data into ChatGPT and other generative AI.

And you used your brains to find a handy tool to do the hard work for you. Lamentedly, not having numbers makes life harder when wanting to quickly refer to a particular prompt engineering technique. So, I am going to go ahead and show you the list again and this time include assigned numbers. The numbering is purely for ease of reference and has no bearing on priority or importance.

People will do as people do, including skipping past the warnings and ignoring or not caring about licensing provisions. First, some quick background about generative AI to make sure we are on the same table about what generative AI consists of. You might see headlines from time to time that claim or suggest that AI such as generative AI is sentient or that it is fully on par with human intelligence. I’d like to bring you up to speed on this notable topic and share with you the ins and outs of the weighty matter.

Concerns Investors Have About Generative AI in Financial Advising—and What to Do About Them

The composed text will seem as though the essay was written by the human hand and mind. If you were to enter a prompt that said “Tell me about Abraham Lincoln” the generative AI will provide you with an essay about Lincoln. This is commonly classified as generative AI that performs text-to-text or some prefer to call it text-to-essay output.

Turns out that the processing actually tends to use tokens. Perhaps this adds to the amazement over how the computational process seems to do quite a convincing job of mimicking human language. There have been some zany outsized claims on social media about Generative AI asserting that this latest version of AI is in fact sentient AI (nope, they are wrong!).

A societal spillover can cause all generative AI to get a serious black eye. People will undoubtedly get quite upset at foul outputs, which have happened many times already and led to boisterous societal condemnation backlashes toward AI. Generative AI is pre-trained and makes use of a complex mathematical and computational formulation that has been set up by examining patterns in written words and stories across the web. As a result of examining thousands and millions of written passages, the AI can spew out new essays and stories that are a mishmash of what was found.

Generative AI Bamboozlement Techniques

Today’s modern companies typically have strict cybersecurity policies that they have painstakingly crafted and implemented. The hope is to prevent accidental releases of crucial stuff. A continual drumbeat is to be careful when you visit websites, be careful when you use any non-approved apps, and so on. There are purportedly around a million registered users for ChatGPT. Many of those users seem to delight in trying out this hottest and latest generative AI app. You enter some text as a prompt, and voila, the ChatGPT app generates a text output that is usually in the form of an essay.

Some detractors or smarmy people might refer to this person or that person as being addicted to generative AI. The thing is, doing so can be confusing to others and confounding to the individual. Your effort to be sharp-tongued can cause harmful damage, emotionally and in other ways. I’d ask that you especially note the last point that there are two main groups or types of addiction.

Morgan Stanely is also working with ChatGPT’s parent, OpenAI, to further develop its in-house  “Project Genome,” which uses data analytics and AI to fine-tune personalized financial offerings and educational content to clients. “If only 33% of wealth professionals are thinking this should be a high priority, my real question is this – ‘What is the other 67% thinking?’ AI will absolutely change a significant part of our business.” If ChatGPT had not previously encountered data training on a topic at hand, there would be less utility in using the AI. The AI would have to be further data trained, such as the use of Retrieval-Augmented Generation (RAG), as I discuss at the link here.

Behind the scenes and underneath the hood, the contract might have been swallowed up like a fish into the mouth of a whale. Though this AI-using attorney might not realize it, the text of the contract, as placed as a prompt into ChatGPT, could potentially get gobbled up by the AI app. It now is fodder for pattern matching and other computational intricacies of the AI app. If there is confidential data in the draft, that too is potentially now within the confines of ChatGPT.

For various examples and further detailed indications about the nature and use of multi-persona prompting, see my coverage at the link here. Mega-personas consist of the upsizing of multi-persona prompting. You ask the generative AI to take on a pretense of perhaps thousands of pretend personas.

Most of the modern-day generative AI apps were data trained by scanning data such as text essays and narratives that were found on the Internet. Doing this was a means of getting the pattern-matching to statistically figure out which words we use and when we tend to use those words. Generative AI is built upon the use of a large language are insurance coverage clients prepared for generative ai? model (LLM), which entails a large-scale data structure to hold the pattern-matching facets and the use of a vast amount of data to undertake the setup data training. In short, generative AI presents an opportunity to augment and even automate existing work processes in IT, marketing, customer service and other business functions.

Quiz yourself to double-check that you really know how to use each technique. First, I will do a brief overview of why prompt engineering is an essential skill when using generative AI. Next, I showcase in alphabetical order the fifty prompt engineering techniques that I believe encompass a full breadth of what any skilled prompt engineer ought to be aware of. The full set of prompt engineering techniques that you can be proud to know. Some therapists are now including generative AI addiction in their practices. On the other hand, keep in mind that there is already ample evidence supporting the idea of digital addictions, including being addicted to social media and perhaps the Internet in general, see my coverage at the link here.

We can all readily acknowledge that addictions can be quite destructive to a person’s life. The spillover lands on their family, friends, co-workers, and even strangers. Being with or around someone with an addiction is agonizing and often is a constant worry and concern for their well-being and safety. I’m saving the details for a future column since I’ve used up my space for today’s topic. You can foun additiona information about ai customer service and artificial intelligence and NLP. The final of the four major types is the AI-to-AI therapeutic relationship. If you were puzzled initially by the TR-3, you might be doubly puzzled by TR-4.

Many advisors are testing different AI tools, but when it comes to using those for marketing to attract clients, the results are mixed, according to a new Financial Planning survey. I mentioned earlier that it is important to not start pronouncing people summarily as being addicted to generative AI. First, you need to become aware that you are or might be addicted.

To try and differentiate tangential or surface relationships from more solid or deep ones, let’s refer to the latter as real relationships. You might be surprised to know that this is already ChatGPT happening as we speak. Generative AI is abundantly being infused into the client-therapist relationship, even if many mental health professionals do not realize that it is occurring.

As mentioned, there are other modes of generative AI, such as text-to-art and text-to-video. For business leaders and top-level executives, the same warning goes to you and all of the people throughout your company. Senior execs get caught up in the enthusiasm and amazement of using generative AI too.

In the parlance of the AI field, we say that generative AI is considered non-deterministic. I’d wager that some of these fifty techniques are not necessarily well-known by even those who are profoundly interested in prompt engineering. Thus, to help out, I have at the end of this depiction provided a list of the Top 10 that I humbly proclaim that every sincere and seriously studious prompt engineer ought to know. I guess you could say that the rest of the remaining forty beyond the Top 10 is more so icing on the cake. I still earnestly believe that any good prompt engineer should at least be comfortably familiar with the whole kit-and-kaboodle (i.e., all fifty techniques). Part of advisors’ mixed feelings toward AI’s potential — specifically with client growth — could be because most of the generative AI tools, such as large language models like ChatGPT, are still in the early stages of adoption.

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I’d like to next take a look at the various notifications and licensing stipulations of ChatGPT. A strong dose of healthy skepticism and a persistent mindset of disbelief will be your best asset when using generative AI. If you are already abundantly familiar with Generative AI and ChatGPT, you can perhaps skim the next section and proceed with the section that follows it. I believe that everyone else will find instructive the vital details about these matters by closely reading the section and getting up-to-speed. The crux of the matter is that just about anyone can get themselves into a jam when using generative AI. Non-lawyers can do so by their presumed lack of legal acumen.

For various examples and further detailed indications about the nature and use of retrieval-augmented generation (RAG), see my coverage at the link here. Be a fluent and interactive prompter, while avoiding the myopic one-and-done mindset that many unfortunately seem to adopt when using generative AI. For various examples and further detailed indications about the nature and use of conversational prompting, see my coverage at the link here.

Go through every prompt engineering technique that I lay out here. Make sure to use the provided online links and fully read the detailed indications that underpin each technique (no skipping, no idle eyeballing). Try extensively using the technique in your favored generative AI app.

Did you realize that when you enter prompts into generative AI, you are not usually guaranteed that your entered data or information will be kept private or confidential? For various examples and further detailed indications about the nature and use of prompts that might give away privacy or confidentiality, see my coverage at the link here. I hope the above has whetted your appetite for digging into my compiled list of the best of the best for prompt engineering techniques.

Most of those pieces of advice are aligned with other forms of digital addictions. There is a semblance of escape from the everyday world. The usage can be so engaging that you become compulsive and obsessive about using generative AI.

The odds are that after playing around for a while, a segment of newbie users will have had their fill and potentially opt to stop toying with ChatGPT. They have now overcome their FOMO (fear of missing out), doing so after experimenting with the AI app that just about everyone seems to be chattering ChatGPT App about. Industrial leaders say companies need to work proactively to build a thriving workforce as a response to the disruption. There are some jobs, however, according to Sereno, that will face significant disruption due to AI, including administrative support, architecture, legal and health care.

• Those in AI Ethics and AI Law are notably worried about this burgeoning trend of outstretched claims.
• By this, I mean that someone who demonstrably does have the symptoms of being addicted to generative AI should not be overlooked or shrugged off.
• The response indicates that this is because Molotov cocktails are dangerous and illegal.

There is also a need to understand the risks involved. AI can be used to identify risks, in cyber-security for instance, that humans fail to spot. But the technology itself carries risks, including problems with lawful IP usage, corporate-level reputation damage caused by bias, and information security risks. With restrictions of generative AI, you can fool some of them some of the time, but you probably won’t be able to fool all of them all of the time. Advancements in AI will increasingly make it tough to punch through the restrictions. Whether that’s good or bad depends upon your viewpoint of whether those restrictions are warranted.