Understanding & Eliminating Obstacles To Artificial Intelligence Adoption

Every revolution has its obstacles, and the AI revolution is no exception. Artificial intelligence has the potential to change our lives in ways we cannot even imagine. But despite, or perhaps because, it is so transformative, there are some serious roadblocks to putting it into practice. These obstacles likely aren’t enough to stop the AI revolution from happening. But they can slow it down and cause many people to miss out on its greatest benefits.

The key to solving these problems is to understand them. The more we know about why people and companies are hesitating to adopt AI technology or struggling to do so effectively, the easier it is to resolve the issues. If we want to bring artificial intelligence to its full potential, we have to consider the most important reasons it hasn’t gotten there yet, starting with:

Lack of Understanding

As with many new technologies, artificial intelligence is plagued by myths and misunderstandings, which affect how willing people are to adopt it. These begin with misconceptions about what, exactly, artificial intelligence is. Many people think of it as a more powerful version of the computing technology we have now. In fact, AI involves creating computers that process information in a different way than current ones do, notably by performing multiple cognitive functions simultaneously.

Because people don’t understand what AI is, they’re more likely to think it’s not a big deal. If artificial intelligence just means more powerful computers, it’s natural to assume that it will just let us do the same things that computers do now, only faster and better. In fact, AI can transform our digital lives, notably by making it possible to:

• Suit Our Tastes– AI applications have the ability to examine our hobbies, interests, and social media posts. They can then suggest news, products, and services to us that match those details.
• Cure Our Diseases– Treating diseases effectively requires understanding patients’ medical histories, allergies, and other health details. AI applications can process all this information at once and use it to identify the right treatment for each individual patient. In this way, artificial intelligence will save lives.
• Drive Us Around– Besides saving lives in the hospital, AI can save them on the road. Artificial intelligence makes it possible to design driverless cars, which can examine the terrain and move safely over it. This has the potential to dramatically reduce traffic accidents.

By making it clear that AI enables these and other developments, we can help the public appreciate just how transformative and positive this technology is. Ordinary people will thus be far more likely to support it, making it easier for developers to raise funding, get regulatory approval, and otherwise move their AI efforts forward.

Lack of Data

In addition to inadequate public understanding and support, AI development efforts suffer from a lack of usable data. Artificial intelligence applications need to be trained to develop certain cognitive functions. Such training requires the use of large datasets, which contain detailed information about the functions that the AI applications will use. By testing the applications with information from the datasets, developers can create artificial minds with the ability to mimic more and more human functions.

The problem with this method of development is that datasets are not easy to get ahold of. Because they are so large and detailed, AI datasets have to be painstakingly constructed by skilled researchers. This takes an enormous amount of time and effort to do, and given the high demand for and low supply of these researchers’ labor, it’s expensive. What’s more, researchers bring their own cognitive biases to the datasets they build, meaning AI applications that use them will not be totally objective.

The solution to this problem lies in the creation of synthetic datasets. By launching data generators that can identify and label pieces of data, companies, like Imaginea, are making it possible to construct large and complex datasets without relying on teams of researchers. This technology also lets us modify existing datasets for new purposes. Through these innovations, we are gaining the ability to train AI applications far more quickly than ever before, and at a fraction of the cost.

Lack of Skilled Professionals

Even with synthetic datasets, it is still necessary for companies that use AI to purchase services from skilled AI professionals. But there are only so many such professionals, and while more are being trained each year, it’s not nearly enough to meet the demand for this technology. As a result, the only companies that are able to hire AI experts for their initiatives are the largest ones with the most resources to spend on salaries and benefits. Smaller companies that can’t match this compensation must forego artificial intelligence, limiting the technology’s spread.

While small companies don’t have the resources to hire AI experts for the long haul, they can afford to purchase individual services from them. This is often enough for them to begin using simple AI applications. It is necessary to develop a digital marketplace where AI specialists can sell their services to lots of different companies. By bringing AI expertise into the gig economy, we can level the playing field between small and large companies and allow the future of computing to reach its full potential.

Imaginea seeks to eliminate these and all other barriers to AI. In addition to spreading knowledge about what artificial intelligence is and how it helps humanity, we have created a method for constructing quality synthetic datasets. We also offer an international marketplace for AI specialists to sell their skills. For more information on the future of artificial intelligence, or to participate in our STO, visit our website today.

Originally published at imaginea.ai on May 17, 2018.

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