Today, as a few dozen times in the last seven years, a recruiter knocked at the door by offering another great position in the Silicon Valley.
As a Computer Vision Scientist.
Now, I may have misled all of them by defining myself as a “Human Performance & Experience Researcher” in my LinkedIn profile. My current role as a “Vision Scientist”, preceded by one as “Principal Human Vision Scientist” may have implicitly triggered their action system, which leads to type the next email to the next lead candidate on the base of primordial spinal reflexes. I believe they try their best, although I also think that reading the basic tags of the profile may exponentially improve their efficiency.
More broadly, this tells me that there is a very little knowledge and understanding of what a Human Vision Scientist is, and how she can provide fundamental insight to tech products.
My goal here is to provide some basic definitions to avoid the next wrong call. But in the process I hope I can also stimulate engineering, design and product teams to wonder whether they may have added value by hiring one or two of these exotic figures, who are weirdly interested in how humans. sense the world.
A few, very basic points may be useful to start the discussion.
- A Human Vision Scientist studies people, not machines. Her job is to characterize the very basic interactions of your product with the user’s vision. Vision Scientists are expert of the cognitive and biological aspects of vision and provide accurate data on the visual interaction of the user with your product by using a variety of robust methods from psychophysics or other methods of quantitative psychology. Other specialists in Human Perception can inform about the interaction of the product with acoustic, tactile or other types of stimulation.
- A User Interface is a visual stimulus(or acoustic, or haptic, or..). As such, it can be seen more or less well, it can distract rather than direct user attention, it can be well seen only by a fraction of users, it can perturb our interaction with the world outside our devices. Therefore, it is important to design product and interfaces to comply with the complex rules of the Human Perceptual System.
- User Experience is limited by the Perceptual Experience. If your product is not well received, and your design team reports data suggesting poor user experience, chance are that something very basic perturbs the user to start with. For example, poor text legibility is a frequent cause of bad User Experience, and the fixes are more scalable or robust if they are based on data and knowledge from Human Vision Science.
- Human Perception is a highly technical field. An expert in human vision needs to go through explicit and implicit learning of Signal Processing, Computer Graphics, Statistics, Math & Geometry, Neuroscience, Experimental Design and a lot more. The very pillars of Computer Vision are indeed rooted in Human Vision Science. But Computer Vision is only an approximation of the sheer complexity of the biological system that support us in our visual tasks.
- Human Vision Scientists are a growing figure in tech. The growing field of immersive technology, like AR/VR, has brought digital interfaces, hardware and software, so close to our senses and body that experts in human systems become essential stakeholders in the development of these products. But there is also growing interest and applications of vision science principles and practices to traditional 2D interfaces. Several people, some with senior status in academic research, have been making the leap in recent years. More and more PhDs in vision science want to keep their profession in the tech industry. I am one of them.
The discussion can go wider and deeper, but this is not my goal. My goal is to help understanding that Vision, or Perception experts, are not only dealing with sensing computers.
So, if you really don’t want to waste time with a bunch of wrong email and calls, next time give a closer look at your candidate profile as you see the word ‘Vision’.
Or, better, go out and search for Human Vision Scientists, as they will add incredible value to your org. But make sure not to bug Computer Vision Scientists this time ;-) !