Human-Computer Interaction Trends

How A.I. can revolutionise HCI and impact consumer engagement?

We have witnessed numerous paradigm shifts for Human-Computer Interactions in every decade. A well-designed computer interface can directly influence how successful the product is, and as different kinds of innovative technologies are emerging today, the study of HCI has also come to a new stage. In this article, we are going to explore the trends of HCI and discuss how businesses specifically can revolutionise their relationship with consumers with the improvement of A.I. technology.

What is HCI?

As a field of research, Human-Computer Interaction studies have been around since the 50s and 60s, when computers were first invented but still not commonly used. The field first developed around the ideas and goals of making computers more friendly to use; Douglas Engelbart, the pioneer of interactive computing, envisioned a future where “humans [could] manipulate and operate computers in different ways”. He would eventually introduce many of the early ideas about how humans would interact with computers, such as the mouse, hyperlinking, on-screen editing, and he even saw the potential of the internet to enable collaboration between teams in remote locations. But it’s not until the 70s, when personal computers were first introduced, that the HCIs began to see a large explosion of innovation. Many of the tools and applications developed during this time, such as multiple windows and high-resolution displays, are still used ubiquitously today.

From the mid-90s to the present day, the field of Human-Computer Interaction has evolved into a professional industry. Today, human factors like user satisfaction, enjoyability, and humanisation are the primary focus for practitioners in this industry, and there is plenty of evidence to suggest that a well-designed UX is fundamental to a product’s success. During an interview with First Round Capital in 2013, Joe Gebbia, the co-founder of Airbnb, openly talked about how they saved the company from zero growth in 2009 by focusing on the importance of UX. Simple changes like swapping the “Bookmark” icon from a “🌟” to a “❤️” resulted in over 30% increased customer engagement. They were able to change the attitude of their designers to start from a user-first perspective and to think of new ideas creatively (First Round Review, 2013).

What Defines Good HCI?

Just as much as a well-designed HCI can influence the success of a product, a badly designed HCI can have catastrophic consequences. In Pennsylvania, 1979, a commercial US nuclear power plant suffered a cooling malfunction, later becoming known as the Three Mile Island Accident. Subsequent investigation and reports into the incident would discover that a badly designed HCI at the control centre was partly to blame for the accident, as the engineers had no equipment to let them know that reactor coolant water was leaking from the reactor coolant system causing the malfunction (World Nuclear Association, 2020). This is still considered to be the worst accident in US commercial nuclear power plant history.

A well-designed HCI should be expected to fulfill the following goals: (i) safety, (ii) utility, (iii) effectiveness, (iv) efficiency, (v) usability, and (vi) appeal. The “safety” requirement is well demonstrated with the Three Mile Island accident, but a “save before exit” function for many designs and editing software is also a good example. “Utility” refers to providing appropriate functions, such as the formula and the chart tools in Microsoft Excel. “Effectiveness”, “efficiency”, and “usability” are similar in that they are the measurements of: how users can accomplish their objectives, how quickly they can accomplish them, and how easy the process is. But perhaps most importantly is “appeal”, which refers to how the users like the interface, and ideas such as first impressions and long-term user satisfaction. When an HCI can meet more of the above goals, there is a higher probability of improving the user’s productivity and therefore the product’s sellability.

Future of HCI

Looking into the future, we believe that the field of Human-Computer Interaction will continue to progress with further advancements in Artificial Intelligence. A.I powered tools and applications are greatly changing the way we can interact with computers, and two particular A.I. skills will have huge implications to HCIs:

Natural Language Processing (NLP)

NLP or Conversational A.I. empowers computers to understand and interact with users in natural human languages, instead of traditional methods of data and coding, greatly improving the efficiency and usability of computers. In essence, we can use English, Chinese, or any other language to communicate, and even have human-like conversations with computers. Being able to communicate with computers with our native language will allow us to operate computers with ease and the complexity of needing to learn coding languages to operate and manipulate computers will be greatly reduced.

Chatbots are an extremely popular tool for e-commerce that is a good example of how NLP creates new forms of Human-Computer Interaction. Although they are still a relatively new solution in the software market, advancements in NLP will continue to increase the utility and effectiveness of chatbots. Already in 2020, companies who had converted their online forms into chatbot conversations saw conversion rates increase by as much as 50% (Paxman 2020).

Computer Vision

Humans and computers will be able to communicate even more effortlessly when computers can reliably process visuals. Computer Vision is another A.I. skill that allows computers to understand the content and context of images, allowing humans to operate computers with gestures or even facial expressions. Computer vision is often applied in technologies such as self-driving cars, allowing the A.I. to recognise and analyze the environment to maintain the safeness of the driver and vehicle.

This A.I. ability also opens up possibilities for more tools like Eye-Tracking, meaning that the computer will be able to track the gaze of humans. This can boost the development of many other technology domains, such as digital marketing, to track the gaze of customers on the website. Eye-tracking also allows people with disabilities to operate computers with their eyes, greatly enhancing the interaction between humans and computers.

A.I. powered HCI in business

The UI/UX industry has exploded in recent times with the emergence of new technologies like Augmented and Virtual Reality (AR/VR), touchscreen, and various A.I. powered solutions. UI/UX designers and developers are encouraged to think of new ways to attract and assist their users or customers, and it is often the deciding factor to determine victory over competitors. Customers naturally prefer to purchase a product that is well-designed and suitable for their personal needs.

Here at Kami, we focus on improving Human-Computer Interaction through research and development in NLP. Our efforts are primarily centred around improving the utility and usability of NLP solutions by creating our custom in-house developed NLP framework that incorporates knowledge engineering with deep machine learning. We have discussed the commercial side of applications for NLP in our previous articles listed below:

Our goal is to empower companies with tools to adopt and develop “Hyper-Personalisation” and “Hyper-Automation” strategies.

Hyper-Personalisation is a strategy whereby large volumes of user data, such as demographic information, purchasing history, and personal interests, are analysed and used to modify, adapt, and generate unique user engagement. Emotional tones, lexical choices, and speech patterns can be varied to apposite the users’ preferences, using natural language generation technology, to create a wholly unique personal experience. According to a study by Accenture, 91% of consumers are more likely to shop with brands that recognise, remember, and provide relevant offers and recommendations to them (Accenture Interactive, 2018). On the other hand, Hyper-Automation is a strategy whereby repetitive and low-value tasks can be automated so that humans are freed to work on tasks that are of higher value to an organisation. Through the use of cutting-edge technologies, including chatbots and language generation systems, human users can start to explore new models of collaboration with computers.

The humanised interaction between users and computers is going to open up enormous amounts of possibilities in the future for the business sector. When controlling computers is becoming more user-friendly, employee’s productivity and engagement will improve significantly. Instead of spending time on repetitive tasks such as categorizing emails and creating invoices, workers can have these tasks be handled automatically in their preferred manners. Meanwhile, customers will receive more efficient and personalised digital services, and will likely purchase the same products or services, essentially improving all business performance.

HCI is not only applicable to a single product, we have also discussed the concept of “New Retail” in one of our previous articles when interactive technologies are inserted into traditional brick & mortar stores to provide a better customer experience. The digital experience inside the traditional stores is not only a gimmick, interaction between the customers and computers during a physical shopping experience can become a lot more in-depth with the help of A.I.


HCI is fundamental to make products more successful, and with the help of A.I., these products will become more functional and effective. Businesses should take advantage of using various technologies and build a personalised relationship with their customers because providing more human-centric services will lead to the improvement of their business.


Accenture Interactive. (2018). Personalization Pulse Check. Accenture.

First Round Review (2013). How Design Thinking Transformed Airbnb from a Failing Startup to a Billion Dollar Business.

Kantarci, A. (2021, March 18). 84 Chatbot /Conversational AI Statistics: Market Size, Adoption. AIMultiple.

Paxman, K. (2020, July 14). The Data Doesn’t Lie: Increase Your Conversion Rates by 50% With Chatbots. Chatfunnels.

Think With Google (2012 September). What Users Want Most from Mobile Sites Today.

World Nuclear Association (2020 March). Three Mile Island Accident.

Intelligent Machine Conversation