Webinar Recap: Demystifying Big Data & AI

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AI is a powerful tool that can help businesses achieve monumental success. For the last few years, AI has been inaccurately depicted as a tool that will steal jobs from humans. The media, movies, and more have consistently created a false image of AI, what the technology is capable of, and what it means for businesses and society. Truthfully, it’s the people behind AI that determine the outcomes of its use  — not the technology itself.

Gonzague Dromard, our head of France, sat down with the co-founder of Siri and Renault chief scientific officer, Luc Julia, for a webinar discussion on demystifying AI and the big data that makes AI function. Here are the top three things we learned from that discussion.

Essentials To Know 

AI is more than just a buzzword and less than the harbinger of the next tech-driven apocalypse. Instead, AI is a tool with the enormous potential to uplift industries and workers worldwide. Yes, this is daunting — but, no, this does not make AI dangerous.

1. AI’s Framework: It’s Older Than You Might Think 

Although AI may seem to be a modern invention or trend, the groundwork has existed for decades. Artificial intelligence and big data are built around maximizing the efficiency of repetitive processes. Leaning into his new role at Renault, Julia highlighted how the car industry has been using automation for decades, starting in the 1960s with the introduction of industrial robots capable of simple tasks like spot welding. Lan Turing’s landmark paper “Computing Machinery and Intelligence” was published in 1950, giving us decades to properly define, create, and deploy early concepts of AI.

Although not as “smart” as some might expect, AI, at its fundamental level, is a repeatable set of rules that a machine follows — an instructional map, but certainly not the driver.

2. AI Does Not Destroy Jobs — It Accelerates Them in New Areas

Among the biggest questions that stymie wider acceptance of AI is whether the technology will replace human workers, destroying the livelihoods of millions of people. Dromard and Julia spent a significant portion of the webinar dismantling this misconception by underlining these AI truths:

  1. There are multiple levels to artificial intelligence. If it becomes possible, we are far from a future where AI will completely replace human workers in most industries since AI relies on repetition — and the world at large is dynamic, not static.
  2. Organizations must be proactive and introspective by identifying where efficiencies could exist and how AI can be used. 
  3. Companies thrive and innovate best when existing teams — with diverse backgrounds and experiences — are trained to use big data and AI.

When applied properly, AI creates entirely new industries and provides existing workers the chance to reskill while working alongside AI systems that make less enjoyable, routine tasks easier to accomplish. Since these tasks don’t change, the big data backing them can perform those tasks more quickly and efficiently than human workers. 

3. AI Programmers Must Counter Personal Biases 

News-making examples of bias within AI systems, such as facial recognition technology and hiring algorithms, have raised legitimate questions about whether AI will always be applied ethically. Dromard and Julia also took on this challenging question with strategies for how to ensure that the big data working in the background mitigates the risk of bias in AI systems:

“If we see that people can use it the wrong way, we have the responsibility to raise the flag. Data can be biased because the people designing and creating the data can be biased.” 

As AI integrates more into daily life, data ethics has become imperative to ensure AI does not harm societal equity.

Take the Next Progressive Step With Big Data & AI

As Julia noted in our webinar, “AI is a tool. We have the hammer.” In other words, if you give that hammer to the right person, innovation will happen. Not all workers will know how to use the tool right away or in the right way, but dedicated and ongoing training can create lasting relevancy for businesses and build loyalty among workers.

Bottom line, people are only innovative if they’re trained with intention. When your teams bring their existing skills to the table — and merge that with newly acquired knowledge — real innovation happens. Watch the full webinar here

Want to learn more about how GA can help you build a data-driven team? Get in touch.