How to Tell the Difference Between Real and Fake A.I.
Artificial intelligence is here to stay. But as governments, companies, and people adapt to the reality of a world with AI, a revolutionary concept has been co-opted into a buzzword. AI as a sales tool has led to false claims and misinformation, making it difficult to parse facts about legitimate AI from the hype.
Here are some tips to help you tell the difference between real AI and fake AI.
AI is predicated on autonomy. It uses neural networks, machine learning, and other tools to create and run production models that not only simulate and predict outcomes, but act based on those predictions. Some analytics companies bill their services as AI-driven, but if a human is required to act on a recommendation made by AI, then it’s not real, independent AI. Useful AI removes the need for human intervention. Predictive technology alone is just that – predictive technology.
It is important to evaluate how much human input is required for an AI-driven platform. Human setup can (and should) be a part of each service – after all, someone needs to set the parameters that dictate AI’s behavior. But any platform requiring daily human operation or maintenance is not true AI. Services that necessitate lengthy training and consulting processes are not selling a truly automated experience.
Most companies offering legitimate AI products will contractually guarantee increased performance. Real AI operates at a level of efficiency that humans are not capable of, regardless of the task it is performing. Be wary of companies that cannot guarantee superior results relative to people or other products on the market. Insights alone are not a measure of useful AI – a service that does the work for you while also providing new levels of understanding is a legitimate AI product.
It is also vital to consider the transparency of the product in question. True AI tools will offer a window into the millions of tasks it performs – if actions are obscured or visible only to the company providing the service, chances are it is not useful AI. Paying for a service that could be a person and a tool performing the tasks that are billed as artificial intelligence defeats AI’s very purpose.
As more and more AI products and services hit the market, it will become increasingly important to identify real-deal offerings in a sea of pretenders. Real AI may be sculpted by humans, but it should perform at a level of efficiency – without any human input – that no human can approach.
Adding A.I. as a Tool in Your Investment Toolbox
One of the only certainties of investing in stocks, bonds, forex, cryptocurrency, or any other type of security is that there is no certainty when it comes to future price movements. Making an investment decision about a trade or a strategy can involve all the data and research in the world, but there still remains an element of chance, and ultimately, luck.
But that does not mean it’s a waste of time to perform diligent research and homework, and to use all of the tools at your disposal in an effort to make informed, smart decisions. More data generally leads to greater conviction, which can also also lead to a higher probability of success.
That’s where Artificial Intelligence comes in. It is a very new tool that until now has not been available on a broad basis to retail investors. The A.I. mentioned in this article can be found on Tickeron.com, and it offers investors a free trial. Tickeron’s idea is to provide retail investors with technology and tools to enable trading with massive amounts of data and analysis. The end result is arming retail investors with a high-powered, virtual research assistant: Tickeron’s Artificial Intelligence. Readers can check out the free trial here: Pattern Search Engine.
Contributor
Sergey Savastiouk, Ph.D. has a degree in Applied Mathematics from Moscow University and has extensive experience as an entrepreneur, investor, manager, and mathematician. His professional expertise is in applied mathematics, mathematical modeling, system and pattern analysis, and software and hardware system integration. He has served as the CEO of several hi-tech start-up companies and nonprofit organizations, which has given him proven capabilities in business strategy for high-tech start-up companies, market assessment, company formation, team building, product development, marketing, and sales. He has published numerous articles in journals and magazines on related fields. As a retail investor, he spent 15 years developing his proprietary trading and quantitative algorithms (now Tickeron’s A.I.), which brought him significant returns in trading the stock market. His current work and goal in founding Tickeron is to bring professional, sophisticated stock market analysis capabilities to retail investors via an easy-to-use interface.
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