 are proving the importance of IBM and Google’s diverse approach to this multifaceted problem){kind=link}
The fast implementation of Artifical Intelligence might have left aside the inherent risks that comes attached to it. AI has proved a very useful tool to provide users a customized experience, however it does so in an aggressive and subtle way that most of these consumers aren’t aware of. The unseen dangers inherent in Artificial Intelligence (AI) are proving the importance of IBM and Google’s diverse approach to this multifaceted problem,
That’s the reason why Brad Shimmin, Service Director at GlobalData, a leading data and analytics company, offers his perspective on this important issue:
“Artificial Intelligence (AI) has already changed the way consumers interact with technology and the way businesses think about big challenges like digital transformation. In fact, GlobalData research shows that approximately 50% of IT buyers have already prioritized the adoption of AI technologies, and that number is expected to jump to more than 67% over the next two years.
“However, there is a growing realization that good AI is hard to come by and such decisions AI makes, may only appear to be correct, when in reality they harbor unseen biases, based on incorrect or incomplete data. Many facets of AI such as Deep Learning (DL) algorithms are in essence a black box, unable to reveal how and why a given decision has been made.
“Over the last two weeks, IBM and Google, both took an important next step by introducing tools, capable of building trust and transparency into AI itself. Both offer highly divergent approaches yet neither solves the problem in its entirety.
“Google’s new tool, named What-If Tool, allows users to analyze a Machine Learning (ML) model directly, without any programming. Intended for use long before an AI solution is put into operation, this tool allows users to readily visualize how the outcome of a given ML model will change, according to any number of “what if” scenarios surrounding the model itself or its underlying dataset.
“Conversely, IBM has taken an operational approach to the problem with its new trust and transparency capabilities for AI on IBM Cloud. IBM’s new tools evaluate the effectiveness of a given model, based on how the business expects it to behave, explaining its effectiveness and accuracy in natural and business language.
“Despite each solution not being enough to solve the overall problem, what these two highly divergent solutions point to, is the necessity of a multi-pronged approach to building trust in AI; first in the underlying data, next in the model and algorithms, and finally, in the final solution running in the wild.”
Hernaldo Turrillo is a writer and author specialised in innovation, AI, DLT, SMEs, trading, investing and new trends in technology and business. He has been working for ztudium group since 2017. He is the editor of openbusinesscouncil.org, tradersdna.com, hedgethink.com, and writes regularly for intelligenthq.com, socialmediacouncil.eu. Hernaldo was born in Spain and finally settled in London, United Kingdom, after a few years of personal growth. Hernaldo finished his Journalism bachelor degree in the University of Seville, Spain, and began working as reporter in the newspaper, Europa Sur, writing about Politics and Society. He also worked as community manager and marketing advisor in Los Barrios, Spain. Innovation, technology, politics and economy are his main interests, with special focus on new trends and ethical projects. He enjoys finding himself getting lost in words, explaining what he understands from the world and helping others. Besides a journalist, he is also a thinker and proactive in digital transformation strategies. Knowledge and ideas have no limits.