The moral side of cloud-based data science
Armed with big data, machine learning, predictive analytics, and unlimited data access, how do we limit the potential for harm?
Data Science – Consider sports betting. Today, many bettors use known and published statistics, mathematical models, and other relatively primitive tools. The idea is to gain a small advantage.
Now let’s look at the world of technology. With the advent of IoT (Internet of Things) and edge computing mashed up with cloud computing, as well as access to all relevant information needed to determine the outcome of a sporting event, we could find a 90 percent success rate for those who know how to leverage cloud technology, data, and machine learning as a force multiplier. What Vegas casino would take a bet knowing there’s a 90 percent chance of paying out?
Of course, cloud computing, data science, and AI are the game changers here. Although we’ve always known how to do this sort of stuff in theory, the needed compute, storage, and AI was either not yet invented, or more likely out of financial reach. This is no longer the case.
Our increasing predictive power creates ethical questions that enterprises will have to consider, such as the capability of insurance companies to determine the probable window of death for a policy holder within a few months. Or the capability of an employer to determine the likelihood that a candidate is a recovering substance abuser.
The argument can also be made that these same technologies can be used for good: the ability to spot strokes or heart attacks before they happen, or reduce traffic fatalities by providing automated ways to determine the likelihood of a crash.
This article originally appeared on infoworld.com To read the full article, click here.
Nastel Technologies uses machine learning to detect anomalies, behavior and sentiment, accelerate decisions, satisfy customers, innovate continuously. To answer business-centric questions and provide actionable guidance for decision-makers, Nastel’s AutoPilot® for Analytics fuses:
- Advanced predictive anomaly detection, Bayesian Classification and other machine learning algorithms
- Raw information handling and analytics speed
- End-to-end business transaction tracking that spans technologies, tiers, and organizations
- Intuitive, easy-to-use data visualizations and dashboards
If you would like to learn more, click here.