December 4th 2018, the 3rd “Manufacturing 2075” symposium held by Cranfield University, this time under the heading: Digital Engineering. Following last year’s subject Materials Future, it was the turn of the intangible technologies that will shape our future. It was clear that due to the fast-paced rate of change in this area, it would be hard to imagine, let alone predict what our lives would look like 57 years hence.
There are challenges facing and regarding humans in a digital world, and it was the two keynotes by Prof. Dale Russell and Prof. Sarah Sharples who took up the challenge and made the attendees think about it.
Prof. Russell spoke about the importance of interface design and how our demands on our environments will drive change and the nature of technological development. Her statement that “if we can imagine it, it is probably being worked on somewhere” and shared a short Post Office Research Station film from the late 1960’s titled: Telecommunications Services for the 1990's. If you look closely, you'll catch sight of fax, video phones, WiFi, and much more. Granted, the pace of change is faster now, but wherever there is a need for something, someone will be working on it, and admittedly, not everything could be in our own interest. We could disappear down any one of the “rabbit holes” highlighted by the TV show “Black Mirrors”, or we could rise and review our systems to move to interdisciplinary design covering:
Ethos – our disposition, character or fundamental values
Insight – the faculty of seeing into the inner character or underlying truth of an issue
Relationship – accessibility and the state of a connection and connective narrative
Interaction – our reciprocal actions or influences
Siloed design and engineering should be a thing of the past, as more of us move to an interdisciplinary skill set – T- shape or E-shaped people, as the Tech Industry likes to call them – Engineers who are familiar with User Experience (UX) and interfaces (UI), designers who understand the engineering required to make their designs work, builders familiar with the technical limitations and correct application of the materials the alternate uses that they might be subjected to…
Reflecting on her comments, the need for interdisciplinary design is becoming increasingly important as we move away from a factory labour-based manufacturing environment to one where less physical is required. We have the opportunity to include people previously with limited access to or excluded from mainstream working life due to physical limitations, gender or geography. We have seen:
GCHQ specifically seek out people with certain kinds of autism for their unique perspective on patterns (https://www.gchq.gov.uk/features/daring-think-differently-and-be-different)
Recognition that dyslexia can be a powerful force to approach work and working life from a different angle (https://www.youtube.com/watch?time_continue=248&v=GHCkpLsIs4E; https://youtu.be/_dPyzFFcG7A )
Colour blindness can force solutions that those who have full colour vision miss or can’t appreciate ( https://uxdesign.cc/what-my-color-blindness-taught-me-about-design-d3009a93ff9c )
Access to education become easier through the creation of on-line programs (http://www.takepart.com/article/2016/07/21/these-15-projects-solving-educations-toughest-problems )
An insistence that environments become more accessible to those with physical limitations – thank you @Sinead Burke one of many voices for inclusion (https://www.ted.com/talks/sinead_burke_why_design_should_include_everyone?language=en)
Awareness of design blindness and techniques to address it- not just in the tech space (https://www.youtube.com/watch?v=JRZY5YH-zk0 )
And many more examples.
With the dawn of large-scale ML and AI, interdisciplinary design will be crucial in addressing the issue of bias. As Council of Europe Commissioner for Human Rights, Dunja Mijatovic said, machines function on the basis of what humans tell them. “If a system is fed with human biases – conscious or unconscious – the result will inevitably be biased.”
Looking at business, there is an increase in the attention that Agile methodologies are having on product development. At the core of Agile is the concept or interdisciplinary teams focused on the customer delivering “value”. Though originating in IT, Agile has also been adapted to other areas; it is these interdisciplinary adaptations and teams that harbour the opportunity to eliminate bias and to address inclusive design.
Prof. Sharples built on this base with her observation of that the worst thing we could do is to “forget the brilliance of humans” and the necessity to address “the Ironies of Automation” as noted in by Lisanne Bainbridge in her 1975 Brief Paper of the same name. For those not familiar with the concept, the ironies of automation can be exemplified as follows:
An automatic control system has been put in place because it can do the job better than the operator, yet the operator is being asked to monitor that it is working effectively
A computer makes decisions quickly, therefore there is no way in which a human operator can check in real-time that the computer is following its rules correctly
An automation designer who tries to eliminate the operator still leaves the operator to do tasks which the designer cannot think how to automate (‘leftover automation’)
There is no denying that these ironies exist, even in the era of Machine Learning (ML) and Artificial Intelligence (AI). Automation is not a goal in itself, but the means to an end, and it is this end that is invariably human-orientated, be it as workers, users, customers, shareholders or suppliers. We should address the ironies of automation to include humans, not rationalise them away as a “weak link”.
For control systems: The recognition that people and technologies form a joint cognitive system, and that there should be the support for the formation of an effective mental model of the process being monitored
For decision speed: Continued understanding into the traceability and accountability of algorithms, along with clarity on what and how data is represented that is used in ML and AI
For left-over automation: A unequivocal recognition of skills, the artificial retention of manual processes for skills maintenance, and initiatives focusing around operator well-being and the prevention of left-over tasks becoming routine and repetitive.
Each of these suggestions is a discussion topic in itself, but at their core all three elements recognise that how we handle automation and the inclusion of humans at the centre of the design, will influence heavily the future we will live in.
Ultimately, we should embrace our “brilliance” at being human beings and focus on our unique skills and capabilities to ensure that the future is as inclusive and interdisciplinary as possible. We must review our value systems to strengthen them, challenge threats to them, and re-align them to a co-existential reality alongside Machines, AI and ML. This is as much an opportunity to grow through collaboration as it is one to step into a “Black Mirror”.
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