Models and Theories in Human-Computer Interaction/The Pace of Innovation and Adoption Is Changing
Technology changes quickly and is rapidly becoming more integrated into everyday life. As new technologies are introduced, people have different levels of comfort with using those technologies. We can describe this comfort level by using the theory of Diffusion of Innovations (DoI) and can describe when groups of people will begin to use the new technologies. We can also use DoI to look at overall technology adoption rates and begin to describe overall attitudes towards technology.
Changing Pace of AdoptionEdit
The Diffusion of Innovations theory includes five levels of adopters ranging from Innovators (those who adopt technology first) to Laggards, who are the last to adopt new technologies. When one looks at the percentage of people who fall into the groups, they form a Bell Curve with most people in the middle and fewer to either side. As people become more comfortable with technology in general, one could expect this curve to shift to the left with the early adoption categories growing in percentages and the later ones shrinking.
The Diffusion of Innovations theory includes a definition of five stages of the adoption process, with the first two (before the decision to adopt an innovation) being gathering knowledge of the technology and persuasion of others. A technology must meet a critical mass of users before it can be seen as being adopted. Due to our increased connectivity today, people are able to research and gather others thoughts on technology more quickly. With people connected via social media, information on new technologies can spread rapidly and people can persuade others by voicing their opinions on technologies. Granted, it is up to each individual to decide if/when they want to begin to use a new technology, but getting to the point of making that decision happens much more quickly so more people decide to make the decision to use the technologies and could be seen as being early adopters.
Advancements in technology build upon themselves and can help to drive overall adoption rates of technology (the adoption of social media driving the ability to research and share opinions on technology is a good example of this). As we advance and technology becomes more engrained in our everyday lives, the adoption rates will only increase until there are many who would be considered innovators adopting new technologies and pushing technology forward.