In the 2018 tech predictions released by GB-Bullhound in December 2017, the most important prediction was the relationship that was changing between politics and technology, followed by cybersecurity, TV in China being overtaken by mobile, translation technology, the end of emails, labor in a global scale, software suite, the new industry 4.0, and the commonality of blockchain regulators and ICO (Initial Coin Offerings). The last piece was AR, Augmented Reality.

Douglas Knight New Canaan would like to direct you to another technology shift that is coming up at the Mixed Reality Lab of USC which is IOA, Internet of Actions. IoA is a digital technology that has a vision of being an effective human partner as we go through the increasing relationship between worlds of mixed realities.

Todd Richmond, the Director and IEEE Member of the Mixed Reality Lab believes that AI (Artificial Intelligence) will be the main driver of personalization which is an important player in IoA.

The Rise of IoA

The major challenge of this journey is going to be trust. As humans increasingly place their faith in tech algorithms, GPS navigation, and online commerce, these are tools in this path rather than partners or collaborators according to the team at Mixed Reality Lab.

The pairing of humans and machine will undergo major R&D over the next two decades and while algorithms shift into decision-making levels that determine life and death, we are going to see a lot of human interactions coming up.

The technology that is going to be developed according to Richmond is one that will be human-focused to help shift the move towards the human challenges of navigating through a fast-paced autonomous and virtualized agent filled earth; and the field of HCI (Human Computer Interface) has to undergo a quantum leap in order to see it through.

For most of us, it is hard to understand how humans are going to communicate seamlessly with AI agents, how we are going to control and exercise commands over a swarm of drones or other AI agents, and how we are going to make sense of the gigantic amount of real sensory data from these devices.

Example of AI to human interaction

There is an increasing use of chatbots that are AI-powered in e-commerce platforms to assist buyers in making smarter online purchases and ensure that a customer’s overall experience is top-notch. Chatbots using AI enhance customer service by using machine learning. Chatbots are now able to respond to simple human questions, but over time, they are going to understand complex queries and solve even complex problems, allowing them to have more meaningful interactions with customers.

According to Richmond, development in technology needs to move to humans at the end of the technology from the current focus that is placed on the device. Despite the common use of user-centric design, technology is focused mostly on widgets and spec instead of improving and enabling the condition of humans.

Douglas Knight New Canaan has been keen to understand the experience of users with the technology, especially when it comes to assessing the intent of the users with technology. Since a lot of tech devices are coming up, with recent developments in creating new technology to be used in training, the most important part is on the human experience. For instance, if a human is put in a simulation and the human makes a wrong decision, if there is no understanding of why the decision was made, there is no actionable information to improve the system or to train the design bit. This will apply to IoA experiences.

If you look at the drones that are being developed for the near future by companies like Mixed Reality lab, the technology is teaming up both humans and machines, and this will play an important role in the future of IoA.

As algorithms become more and more synonymous with our daily routines and become part of our decision-making process, it will be vital for us to understand why an algorithm will take specific action and why a user takes another share of the actions. Additionally, the algorithm will also explain the things that are happening.

Now, back to our contentious topic, trust. If as humans we are not able to trust the machines that we have presented, it will be hard for us to engage with the tech. Knowing how we will build trust and pair humans and machines will be a very important step, as it will lead us into designing systems that will expose the story behind the actions of the systems.

In Summary, we learn and understand through stories, and the tools of representation and abstraction are important for making sense and exploring complexity. The best tech that can come up can be useless if it cannot help in discovering and telling a story that is in the complex data.