Human-machine integration is a state where machines can augment humans with the capabilities which are currently specific to machines. They act as a powerful, invisible force that augments human intelligence and enhances decision-making, blurring the overall distinction between machines and humans. To reach there, we have many hurdles to cross. I believe the two mentioned below are the big ones.

Fluid Communication

The key to successful human-machine integration is a state of effortless interaction, where humans are able to leverage the capabilities of machines without having to consciously direct their attention. This is in contrast to the way we currently interact with technology, which often requires focused and deliberate effort. In a state of true human-machine integration, the interaction between humans and machines will feel seamless and intuitive, allowing for greater efficiency and productivity.

To reach HMI, we need to make the interaction between humans and machines as natural and unobtrusive as possible, allowing humans to focus on what's most important to them while still benefiting from the capabilities of machines. We need to create a more holistic approach where machines are seamlessly integrated into our lives. The goal is to create a world where technology is not separate from us, but rather part of us. We can tap into the power of machines without having to think about it.  

Designing for human-machine integration is about more than just building powerful machines, it's about understanding how humans think and work. We have to consider the ways our brains process information and interact with the world. By designing systems that align with our natural abilities, we can create truly intuitive and empowering experiences. This is a complex challenge, but the rewards are great: we can create technology that feels like an extension of ourselves, rather than something we have to adapt to.

We believe one way to solve this can be via tapping the power of peripheral attention. Building devices that utilize peripheral attention allows for a more natural and intuitive interaction between humans and technology. By engaging the user's peripheral vision, these devices can provide information and support without distracting from the primary task at hand. This can lead to a more seamless and efficient experience, as users can access the information they need without having to shift their focus away from what they're doing.

There is obviously a contradictory argument which is drawn from the concept of extended mind. It states that our cognition doesn’t end with our brain, it includes all the material things we interact with during our work. There's a deeper question here about the nature of technology and how it relates to human cognition. As we automate more and more tasks, do we risk losing some of the benefits of completing those tasks ourselves? To answer this, we might need to look at the technology again. The idea is that we never need to do the middle tasks, because the objective is something else, and our purpose is to reach the objective. The middle tasks are in this way in the current technology norm. Can be completely different in a different technology norm. So, our focus should always be to reach the objective an not worry about the intermediate tasks.  

Machine Perception

The other most crucial aspect of Human Machine Integration is giving the perception and interpretation capabilities of humans to machines. This includes the ability to recognize and understand subtle changes in facial expressions, body language, tone of voice, and other nonverbal cues. Machines will also need to develop an understanding of the context and significance of these cues in different situations. We need machines that can understand the complexity and nuances of the human experience so that they can effectively interact with us and support us in our daily lives.

While machines have made impressive progress in recognizing and categorizing information like images and sounds, there's still a long way to go before they can perceive the world in the same way that humans can. This is partly because machines lack the ability to interpret the context and nuance of the data they perceive. For example, a machine can recognize that an image contains a market, but it may not understand the significance of the people, the activity, and the mood that the image conveys that a 10-year-old can point out.

Machines may need to process information in new ways in order to achieve human-like perception. This could involve a shift away from the traditional method of processing each sensory input separately and instead developing a way to process multiple inputs at once and store the resulting information in a more flexible format. We might need to develop new methods of storing the information in more efficient ways. This may involve novel approaches to data storage and processing that take into account the interconnected nature of information in the real world. So, that the retrieval, and context can be built effectively.

The ability of ambient systems to provide richer and more varied sensory inputs can significantly speed up the process of human-machine integration. By providing a wealth of data about the environment and the user's context, ambient systems can enable more sophisticated and natural interactions between humans and machines.

As we move towards a world where these systems are ubiquitous, it's essential that we consider the implications for privacy and data security from the outset. Ambient systems have the potential to gather and analyze an unprecedented amount of data about individuals and their environments, which raises significant concerns about data privacy and security. Therefore, it's imperative that we design these systems with privacy as a core priority, rather than as an afterthought.

The ultimate goal of human-machine integration is to achieve decision intelligence, a state in which humans and machines collaborate to make informed and effective decisions. This will require a high level of trust, communication, and transparency between humans and machines. With proper safeguards and ethical frameworks, decision intelligence has the potential to greatly improve the quality of human life.