Source: aithority.com
Despite the widespread adoption of AI, there’s one misconception that still affects Machine Learning enterprises. Consumers wary of new Machine Learning technology – 72% of Americans, according to one study – often have a notion of AI as a monolith, with a single all-knowing algorithm controlling everything from our self-driving cars and smart refrigerators to the very stars and beyond.
Of course, AI isn’t an omnipotent single entity, and its uses vary greatly even within a single industry. In fact, the way one company develops its own algorithms for Machine Learning may work best collaboratively, exploiting other organizations’ tech expertise, domain knowledge, and workforce – the fundamental pillars of usable AI.
Companies that work collaboratively not only have a chance to right the public’s perception of AI, but also increase their effectiveness via partnerships. Here are some of the ways bringing AI companies together increases results beyond what’s possible when working alone.
The Varying AI Skill Sets
Any groundbreaking technological change – from the first Industrial Revolution to the adoption of personal laptops in business – creates a fear that current low-skill workers will be left behind. The concept of an AI replacing these jobs – with supervision from a few high-skilled workers – is easy to grasp. It’s also wrong.
According to the World Economic Forum, AI is expected to replace 75 million jobs with 133 million new ones. And while these jobs aren’t a one-to-one exchange – lost data entry jobs do not directly translate into data analyst positions – the fact remains: AI needs people of all skill levels working in concert to achieve its promise.
A company like CloudFactory enables thousands of workers in developing countries to have access to the fast-growing AI job market. Their trained workforce is the human-in-the-loop face of AI. Yet such a workforce needs to have access to a world-class set of AI-powered software tools that enable workers to effectively train their Machine Learning models. These tools need to be cutting-edge, but also approachable to the average worker. Deepen AI, a company with deep expertise in developing best-in-class annotation tools, was the perfect fit to partner with in order to bring the world the benefits of Human-AI collaboration.
It’s this type of partnership between companies that benefits clients, workers, and the end consumer as well. A multifaceted approach to collaboration improves outcomes across the board.
Humans and AI: Working In Tandem
Self-driving cars, Medical Imaging diagnosis, Predictive Intelligence – in all the fields where AI stands at the forefront, the human element behind these technologies remains just as important. It’s only with the guidance of experienced workers – be they laborers, technicians, engineers or otherwise – that these AI technologies come into their own via greater adoption.
The collaboration between AI companies is, in a notable way, similar to the relationship between humans and AI. Companies that strike partnerships rely on each other’s tactics and data to improve Machine Learning models and create new opportunities for their employees. It’s a mutually beneficial collaboration not entirely unlike, say, a hospital using Machine Learning to aid in disease diagnosis.
As AI grows to affect more and more industries, the rate of adoption will be affected by how comfortable users and customers are with working alongside the tech. This is done through making the tools more accessible, but also by emphasizing the power of working with AI, rather than against it.
The Difference In Our Daily Lives
Partnerships between AI companies go a long way toward helping the public understand the tremendous benefits. When AI tech is developed in a way that brings both humans and AI companies together, the breakthroughs are far more innovative than before.
In a partnership like that between Deepen and CloudFactory, customers have the chance to see just how powerful AI can be when implemented in a collaborative manner. These sorts of alliances help to demystify AI in a way consumers not only understand but appreciate.
When AI and humans work together, the results end up beyond what we currently expect. It’ll take more collaboration between AI companies to get there, but the fruits of this labor are there for companies willing to work together to reach them.
