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The promise of machine learning democratization

Machine learning and AI, seamlessly embedded in technology, will make the world greener, safer, healthier, and more secure

The promise of machine learning democratization

Machine learning and artificial intelligence (AI) were once concepts relegated to only the most optimistic observers, much like self-driving electric vehicles and smartphones once were. But if it isn’t obvious, the times have changed. Today, machine learning and AI—along with the immensely powerful data collection and analytics tools that power those processes—are a mainstay of modern life. Every day, people interact with products and services powered by some of the world’s most groundbreaking technology. In retail, social media and telecommunications, finance, architecture, manufacturing, aerospace, and more, machine learning and AI are informing, impacting, and shaping the present and future.

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But machine learning, AI, and data science tools have historically been undemocratic, inaccessible technologies, meaning that only the most advanced users in select organizations and industries could utilize them. This is partly because these technologies are complex, as is getting the high-quality, abundant, and secure data that’s crucial to their success. In addition, it can be challenging for IT departments within organizations to open the data sources, operating systems, and deployment technologies that facilitate the implementation of enterprise-wide machine learning and AI.

That said, today’s machine learning, AI, and data analytics tools are easier to use than ever, and are only becoming more accessible. Additionally, organizations—even small ones—have access to more data than anyone would’ve imagined a few decades ago, giving them the information they need to build machine learning and AI strategies that can make their operations, products, and services more efficient, more cost-effective, and better for customers and employees alike. Moreover, more students and professionals are using machine learning, AI, and data analytics software, which gives organizations more talent to choose from when building teams that can turn concepts into action. In other words, there’s never been a better time to invest in machine learning and AI.

ACCESSIBILITY AND DOING GOOD

Indeed, machine learning and AI is a game-changer, and provides mind-boggling ROI when supported by a solid team of data scientists, analysts, and technology that ensures it can evolve and grow. And today’s machine learning and AI software is also more transparent than ever, often incorporating explainable AI features that show users exactly how the algorithms and technology is interpreting, organizing, and acting upon the data it’s drawing from. But most importantly, the proliferation of low-code and no-code machine learning and AI technology has opened doors to users who otherwise might not have the technical expertise needed to craft strategic models. By giving non-experts—who are often closer to an organization’s tactical operations—access to technology that can help them apply intelligent, data-driven insights, organizations can rethink the way they operate. From finance departments to HR, marketing to sales, engineering to risk analysis, there are more ways to use machine learning and more people that can use it.

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But while it’s easy to sing the praises of new, exciting technology, every organization (and layperson) should be thoughtful and ask themselves: Why democratization? After all, giving more users access to vital data can create potential security risks, and giving non-data scientists the freedom to create machine learning models can lead to potentially life-altering mistakes—especially in industries that greatly impact people’s well-being like healthcare, insurance, and finance. The answer is that democratization can also enable a flood of groundbreaking innovations that do immense good, that make people’s lives healthier, safer, more sustainable, and more secure. The world only has so many data scientists – if more people (non-data scientists) in more industries have machine learning and AI know-how in their toolkit, it gives them the ability to combine their domain knowledge with powerful tools that can help them achieve their goals and create better services, products, processes, and experiences for everyone.

SEAMLESSLY MAKING THE WORLD A BETTER PLACE

Bear in mind that the democratization of machine learning, AI, and data analytics won’t happen overnight – but the gears are turning, and the world’s largest players and most innovative small startups alike are laying tomorrow’s AI-powered foundation. As the technology continues to grow and develop – along with people’s ability to conceptualize and implement it – it’ll only become a more integral aspect of modern life. In the near future, it’s likely that machine learning and AI will be embedded into our technology so seamlessly we forget it’s there. Much like a self-driving car tracks movement, visualizes road conditions, and detects signs and signals all thanks to data and machine learning, it’s possible tomorrow’s bicycles and trains may do the same. The same goes for tomorrow’s credit lending industry, healthcare operations, emergency response infrastructure, and more. In all, organizations and users should be thoughtful and thorough when implementing the machine learning and AI tools of the present and future, but it’s also an opportunity to make tomorrow’s world a safer, greener, more accessible, and more efficient place.

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