Sergey Savastiouk's Avatar
published in Blogs
Feb 27, 2021

Are Business Leaders Taking an Ethical Approach to A.I.?

Powerful, functional tools – like machine and deep learning – are becoming commonplace within businesses, governments, and more. But every positive story seems to be met with equal outpourings of concern about job loss, wealth stratification, and Skynet-esque machine domination.

There are positive signs that businesses recognize their role in assuaging these fears, according to a recent study conducted by SAS, Accenture, Intel, and Forbes Insights. “AI Momentum, Maturity, and Models for Success,” based on a global executive survey of 305 business leaders, reports that leadership is both aware of and actively taking steps to ensure that AI is used ethically and responsibly at their respective companies. 72 percent of businesses around the world have adopted AI; of these companies, 70 percent offer training for staff and 63 percent have functional ethics committees to oversee AI-related issues. 92 percent of “AI leaders” in these organizations receive some type of ethics training – chief information, technology, and analytics officers included.

Some organizations have created AI-oversight positions, including study-contributor Accenture Applied Intelligence. Rumman Chowdhury, the responsible AI lead there, says that organizations realize the seriousness of potential AI issues and “have begun addressing concerns and aberrations…such as biased and unfair treatment of people.” Doing so means enjoying AI’s benefits while embracing a “do no harm” ethos, which Chowdhury believes includes providing “prescriptive, specific and technical guidelines to develop AI systems that are secure, transparent, explainable, and accountable” – all in an effort “to avoid unintended consequences and compliance challenges that can be harmful to individuals, businesses, and society.”

There is additional positive news: 74 percent of AI leaders “reported careful oversight with at least a weekly review or evaluation of outcomes”, while 43 percent have implemented processes for “augmenting or overriding” results found to be questionable through the review process. But there remains room for improvement, and advances in AI (as well as increased adoption) mean businesses are responsible for keeping up. Yinyin Liu, who heads Intel AI’s data science division, believes understanding AI “enables effective human oversight”. “Algorithm transparency and accountability, as well as having AI systems signal that they are not human, will go a long way toward developing the trust needed for widespread adoption,” says Liu.

Trust – between business and customers, and between employees and AI – may be the single most important driver in encouraging companies to practice ethical AI use. 60 percent of businesses that have or plan to deploy AI “are concerned about the impact of AI-driven decisions on customer engagement…that their actions will not show enough empathy or customers will trust them less.”

Functional AI is still a relatively new phenomenon, with all the challenges inherent to that newness. Forbes Insights research director Ross Gagnon says “…the question executives should be asking themselves is not whether to deploy AI, but how quickly?” Doing so ethically will mean maintaining the trust of their customers and employees – and ensuring a bright and successful future.
 

If You’re Wondering When A.I. Will Start Making Market Predictions…

Guess what – it already is. Hedge funds and large institutional investors have been using Artificial Intelligence to analyze large data sets for investment opportunities, and they have also unleashed A.I. on charts to discover patterns and trends. Not only can the A.I. scan thousands of individual securities and cryptocurrencies for patterns and trends, and it generates trade ideas based on what it finds. Hedge funds have had a leg-up on the retail investor for some time now.

Not anymore. Tickeron has launched a new investment platform, and it is designed to give retail investors access to sophisticated AI for a multitude of functions:

And much more. No longer is AI just confined to the biggest hedge funds in the world. It can now be accessed by everyday investors. Learn how on Tickeron.com.

John Jacques's Avatar
published in Blogs
May 16, 2022
A.I. Stock Market Predictions: Head & Shoulders

A.I. Stock Market Predictions: Head & Shoulders

Statistics for the Head-and-Shoulders Bottom Pattern The days where only hedge funds used algorithms to trade stocks are officially over. Now retail investors can use Artificial Intelligence (A.I.  Here’s an example of the algorithm in action: Late last year, Tickeron’s A.I.
Edward Flores's Avatar
published in Blogs
Apr 29, 2022
How to Become the Millionaire Next Door

How to Become the Millionaire Next Door

The Golden Gate Bridge is always a fixture of these walks too, one of man's most beautiful creations.  As we were walking, at one point she turned to me and said, "Man, I'll never have a million dollars."" My girlfriend is 27 years old and works as a graphic designer, making about $75,000 a year.
Sergey Savastiouk's Avatar
published in Blogs
May 16, 2022
When Is the Next Recession Coming?

When Is the Next Recession Coming?

However, we also know that economists predicted 22 recessions out of 11 that took place since 1945. Are there real recession signs we should watch for?Indeed, the answer is yes, and here are a few very important ones: The first one is almost obvious and known to everyone – it is the Fed.
Sergey Savastiouk's Avatar
published in Blogs
Mar 14, 2023
How to Start Trading Penny Stocks

How to Start Trading Penny Stocks

Penny stocks have long been marginalized within the professional investment community, oftentimes being painted with a broad brush of simply being “too risky.” Leonardo DiCaprio’s depiction of the penny stock peddling conman, Jordan Belfort, in the Wolf of Wall Street certainly didn’t help.Here are four reasons to start trading them now. Reason #1: Let’s State the Obvious -- Penny Stocks are Cheap A single share of Apple Inc. costs over $350.
Dmitry Perepelkin's Avatar
published in Blogs
Mar 14, 2023
5 Habits that Lead to Successful Investing

5 Habits that Lead to Successful Investing

To consistently make money in this industry, you need emotional fortitude, an analytical mind, and a willingness to self-reflect. Despite trading and investing being two different activities, these principles can be applied to both.Conversely, investors with good habits often become great traders.  Rather than full sentences for titles, we’ve labeled each of our top-five investing habits using a single word principle.
Allana's Avatar
published in Blogs
Mar 23, 2023
What’s the Difference Between Data Analytics and Machine Learning?

What’s the Difference Between Data Analytics and Machine Learning?

Artificial intelligence (AI) technology is developing rapidly.Data mining can deliver raw numbers, but it does not necessarily provide actionable insights. Structure is necessary to taking abstract information and extracting commonalities, like averages, ratios, and percentages.
Sergey Savastiouk's Avatar
published in Blogs
Mar 13, 2023
4 Tips for Fast, Effective Stock Analysis

4 Tips for Fast, Effective Stock Analysis

With just a few clicks, an investor can search for individual stocks, categories of stocks, sectors, or investment themes, and then he or she can conduct a full range of technical and fundamental analysis within seconds.All powered by Artificial Intelligence.  Below, we give you 5 tips for fast, effective stock analysis using Tickeron’s Screener.
Sergey Savastiouk's Avatar
published in Blogs
Mar 20, 2023
5 Golden Principles in Investing

5 Golden Principles in Investing

You have enough faith in that stock, based on research, that the return will equal or exceed the investment.  Do unto others.The principles outlined here will ensure that happens.  Principle #1: Diversification Investors can’t be one-dimensional when constructing a portfolio.
John Jacques's Avatar
published in Blogs
Mar 24, 2023
If Hedge Funds are Using AI to Invest, Why Shouldn’t You?

If Hedge Funds are Using AI to Invest, Why Shouldn’t You?

Some of the world’s biggest financial institutions have devoted multi-million dollar budgets to developing algorithms that can find patterns in the market, identify trends, and perform automated trading designed to take advantage of even the smallest price movements. The AI revolution is so big that as it stands today, the world’s five biggest hedge funds all use systems-based approaches to trade financial markets.Indeed, quantitative trading hedge funds now manage $918 billion (according to HFR), which amounts to 30% of the $3 trillion hedge fund industry – a percentage continues to grow with each year that passes.
Sergey Savastiouk's Avatar
published in Blogs
Mar 15, 2023
The five most important Lessons Learned After 10,000 hours of Trading