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Introduction to human-centered AI and machine learning

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Despite the overflow of movies and books about robot apocalypses, human-centered AI demonstrates the increasing importance of the relationship between humans and AI. As an emerging discipline, human-centered AI comes with a statement: No matter how rapidly AI evolves and no matter the industry it operates in, augmenting and elevating human input is a greater value-add than its downright banishment. The idea of human-centered AI can otherwise be interpreted as a set of systems that are always evolving/learning thanks to human involvement. Direct examples of human-centered AI in practice range from medical industry, where models still need an upper hand to perform surgery planning, to advanced cybersecurity practices where humans can oversee security measures to prevent data leakage, etc.

human-centered ai and ml

Having introduced human-centered AI in theory, we know what you are still wondering about: the concept sounds great and all, but what does it do? How can I benefit from it? We’ll answer that and more in the coming sections:

  • Why human-centered AI?
  • Implementation and important steps
  • Benefits of human-centered AI
  • Final thoughts

Why human-centered AI?

From a strictly business standpoint, one can benefit from human-centered AI in several ways.


The human element brings in an added layer of supervision over different stages of model development. That stirs up the credibility of the following:

Credibility to the model: The main purpose of AI is to benefit humans, and resorting to a humanistic AI method simply places more work on technology while still grasping into human input. In this respect, significant processes are still handled by an AI model, and the human element is still there without handing in full control to the technology.

Credibility to the data: The human-centered AI solution permits the development of knowledge on a larger scale without negotiating data integrity or accumulating human assets.

Conversant decision-making process

Let’s get one thing out of the way, human-centered AI will not be replacing humans, yet it will enrich human abilities through smart and human-informed technology. As it combines both machine learning and human input, human-centered AI allows businesses to make smarter decisions and improve their tactics and solutions to any encounters.

decision-making process

Increased software and product-building

As human-centered AI introduces behavioral science to technology, developers and product designers can tap into user behavior and unconscious patterns to build products tailored to their customer needs and offer amenities.

Implementation and important steps

In practice, human-centered AI is all about balance. You should be mindful of where it’s most effective to work in the human element in model development or deployment and plan accordingly. A few things you might want to consider:

Inclusive team setup

A typical example of introducing team diversity is having team members from different demographics and geographic locations, which, however, comes at a cost: if you’re bringing that diversity to a team of, say, annotators, there’s a risk of introducing cultural bias to your dataset along the way. Although your team is more inclusive now, it is crucial to have proper instructions in place since each annotator/engineer can carry their own culture-specific bias into the model.

Will humans initiate bias?

Being aware of biases is essential in AI development as it can affect your model performance in more significant ways than you could imagine. In fact, bias can be introduced in multiple ways. The annotators’ case above is only one example where bias serves as a by-product of inclusivity, but the reverse can happen too. Meaning, there are cases where inclusivity, or more particularly humans-in-the-loop, can prevent or mitigate bias. The very same annotators have the ability to control your model’s prediction accuracy and, in turn, suggest improvements that might reduce prediction errors. Take another instance; even if your bias is algorithmic, the choices you make when optimizing functions can initiate/block potential biases. So? Having humans embedded in your pipeline in the right place and at the right time can be a defining factor.

Having clients test your model

As the main priority of human-centered AI is the human experience, you should always consider your clients' perspectives and make sure your model affects their lives positively. In order to meet these goals, you should have a clear understanding of who your customers are, how they are going to implement the technology, and whether it will satisfy their needs or not. Having clients involved in the testing and validation of a model-building process could turn out to be a clever way to receive critical feedback from your end-users and make sure that your prototype meets their expectations.

Benefits of human-centered AI

The use of AI and its impact on our shared future is bound to our moral and ethical systems. We must support AI that’s rightful and provides a net benefit to all of its users, which is where responsible AI comes into play. That nonetheless deserves a whole separate article. For now, let’s move on to the firsthand benefits of human-centered AI:

Modified customer experiences

Whether it is a social platform we are engaged in or a personalized offer we’re receiving from an eCommerce store, we, as users, are more likely to be pleased with the experience when it’s tailored to our personality and preferences. Recommender systems, for example, take the users’ knowledge or demonstrated activity towards a product to recommend new ones. Here, AI is human-centered in that it relies on user behavior, analyzes patterns, and learns from them to offer the best possible experience.

Industry-specific predictions

Human-centered AI offers a stance where neither the machine nor we humans are fully autonomous. The resulting balance affects each industry in its own unique way. For now, let’s crank up the microscope to the following sector:

Healthcare advancements: Stanford’s recent research estimates that public health outcomes will be significantly improved as human-centered AI and medical technology blend perpetuates. “There are AI tools that are working on adapting existing drugs to fight newer illnesses like Covid-19. BenevolentAI, based in London, is doing well in advancing drug development by analyzing scientific literature.”

healthcare advancements

Digital marketing and ads: AI-powered ads will bring in a refined experience to users far beyond the limits of image and video layouts. Two-way messaging experiences right within digital ads will become progressively common, and users won’t have to navigate to a third-party site to shop items.

Enhanced cybersecurity: Identifying threats and monitoring fraudulent behavior will be much easier and faster as human-centered AI taps into cybersecurity. When suspicious activity is navigated, AI chatbot clouds can offer key choices to react to hacking attempts promptly.

Final thoughts

By now, it is safe to say that we have covered the question of what human-centered AI is and its most important aspects. The bottom line—machine learning and AI grab our skills as thinking creatures and flourish our ideas into a top-performing technology that serves us back. To give a concluding answer to the question of how can AI benefit humans, we should find an answer deep down from ourselves as we are the ones responsible for the computational sensing of human-centered AI, its method of operation in a transparent matter, its ability to serve our human needs, and most importantly, its respect for our privacy.

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