Bright Ideas Workshop and Competition

It’s still possible to register to the Bright Ideas Workshop! Click here to secure your place (and a free slice of pizza). In this workshop, Kingston University students will receive support in preparing their entries to the Bright Ideas Competition.

Bright-Ideas-e1459414208510

In addition to being a module requirement for Design Thinking, the Bright Ideas Competition is a great opportunity to receive feedback on your business ideas, and to fund your start-ups. The University offers generous prizes of up to £1,000 for winners!

Need some inspiration? Check out last year’s winners!

performing change

Performing Change was one of the runners-up in last year’s Bright Ideas Competition (image credits: Enterprise)

 

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Understanding AI and its implications

Do we understand AI and its implications well enough?

Are you with Elon Musk who believes AI could lead to WW3 and is urging for AI regulation, or are you leaning towards Bill Gates’ opinion that we’re all panicking?

“The government of UAE appointed its first Minister of Artificial Intelligence in October, days after the UAE’s 2031 AI strategy was unveiled. Omar Bin Sultan Al Olama, formerly the Deputy Director of the nation’s Future department, will take on the role. The government aims to harness AI to increase the GDP by 35%, reduce government costs by 50%, implement a robot police force, and improve education by 2031. These plans reflect the UAE’s desire to be the “most prepared” country for artificial intelligence, according to Prime Minister Shaikh Mohammad.

This is the nation that just released plans to establish a 600,000 person-strong city on Mars by 2117. Clearly the UAE isn’t waiting around for the future to arrive. So when a government as future-focused as this one establishes an entire ministry devoted to AI, you’d better believe that this technology is significant and essential to master.” (via TrendWatching.com)

In other news, Sophia the robot is now a citizen of Saudi Arabia and you can watch her speak about her feelings to Reuters’ at Web Summit in Lisbon. This makes Saudi Arabia the first country in the world to grant citizenship to a robot.

Also, “meet the high schooler shaking up Artificial Intelligence” with no undergraduate and graduate degree, see how farmers in India use AI to help them with their crops, laugh as scammers get frustrated with an AI chatbot, and despair over ethics of AI development.

Our MACE16 student Michelle Petersen decided to develop her own understanding of the AI agenda as part of her MACE Personal Research Project, and I am pleased to welcome her to the BS7705 Mapping the Creative Economy class today to talk about her work on “What role can machine learning techniques play in the film industry; and how do UK film practitioners appraise machine learning in filmmaking?”. Michelle’s research tackles a complex topic but delivers real accessible understanding. Michelle presented her research at the 16th International Colloquium on Arts, Heritage, Non-Profit and Social Marketing organised by Kingston Business School and the Academy of Marketing 8 September 2017.

Do you think we understand AI and its implications well enough?

The NOT SO SMART WATCH by Shed Simove

Sheridan ‘Shed’ Simove gave a brilliant speech at Enterprise! Insights last night. The provocative author, entrepreneur, and speaker offered useful tips for prospective entrepreneurs: look at other industries for inspiration, borrow concepts to bring into your own industry, and break the rules of the game. He underscored the importance of attending trade fairs, using visuals to pitch ideas, and having prototypes to ‘touch and feel’.

Among other ground-breaking ideas, Shed is the proud inventor of Shinder: A dating app in which there is only one guy available (himself). The slogan is quality, not quantity – a provocation that calls into question our hyper-competitive online environments. Shed’s controversial idea is to create a ‘safe harbor’ in which one cannot fail, but only be the first in a market of one. Shinder has gone viral, and has been a success – except for a legal battle started by the giant Tinder! But as Shed has noted, “it’s unlikely that the female population will stop using Tinder and start using Shinder” (BBC, 2017).

My previous blog post “Theories in Practice” used Apple Watch to exemplify different logics – deduction, induction, problem solving (aka abduction-1), and abduction. Interestingly, Shed Simove came up with a new product called The Not So Smart Watch (a Pears Production):

Cheapest Smartwatch ever? The NOT SO SMART WATCH™ from Shed Simove

Which is the logic behind the invention of the Not So Smart Watch? Deduction, induction, problem solving, or abduction? Big (fake) prizes to all those who give the right answer in the comments!

And if you have missed Shed’s talk yesterday, here’s a video on how to unlock your creativity:

3 ways to have amazing ideas: Shed Simove at TEDxStPeterPort

Theories in Practice: Part 1

We have started our journey with an overview of theories that can be premised on the practice and the study of design thinking. In particular, we have discussed Cultural Historical Activity Theory (CHAT) and formal logic. This and the next post aim to crystallize fundamental learnings about these theories, through a series of practical examples.

Let’s start with formal logic! This was first introduced by Peirce (1839-1914), and was then taken up by Dorst (2011) to explain the difference between analytical thinking and design thinking. Dorst (2011) aimed to overcome misconceptions about design thinking (e.g., ‘it’s just post-its and stuff’), by going back to the roots of the term ‘design thinking’. This implied using formal logic to understand how designers think, and how this differs from business.

In short:

Analytical thinking is typical of business, and was derived from the sciences. It is comprised of two main logics: deduction and induction.

In deduction, we can determine a result with little error. We know the working principle (how), and we just need to apply it to our object (what) to determine the result. For example, let’s assume that Apple wishes to calculate the market share of its Apple Watch vis-à-vis other smartwatches. They know the formula to calculate the market share, and have a clear object onto which this formula can be applied (Apple Watch).
What: Apple Watch
How: Market share formula (Total sales of your company / Total sales of all company)
Result: https://androidandme.com/2017/05/news/tizen-overtakes-android-wear-in-smartwatch-market-share/

In induction, we can predict a result (with a greater degree of uncertainty). Here, we know the object (what) but need to find out the working principle (how) to predict the result. For example, let’s assume that a marketing professional is trying to increase sales for Apple Watches. They analyze data and find a pattern suggesting that stores in small towns generate higher sales than stores in large cities (per square foot). They can inductively posit that small towns are a more valuable market for Apple Watches; and define their ‘how’ in terms of targeting small towns.
What: Apple Watch
How: Target small town
Result: Likely increase in sales

As compared to deduction, induction involves some creativity in the development of a working principle (how). Induction is, thus, the ‘bridge’ between analytical thinking and design thinking.

Design thinking is a novel paradigm that has the potential to change the world of business. Derived from the world of design, it builds upon two main logics: problem solving (or abduction-1) and abduction. There is a fundamental difference compared to analytical thinking: In problem solving and abduction, we are not thinking in terms of results, but in terms of expected value for our customers.

In problem solving (a.k.a abduction-1), we know the expected value that we want to generate for our customers, we know the working principle (how) to generate such value, but we still need to find out the object (what) that can deliver such value. For example, let’s assume that Apple needs to develop an Apple Watch that is water-proof: Here, the expected value is the customer being able to wear an Apple Watch under water, and the working principles are offered by previous models (e.g., ‘splash-proof’ Apple Watch). The designer will have to create the new water-proof Apple Watch.
What: Water-proof Apple Watch (to be created)
How: Improving the splash-proof Apple Watch
Value: Swimming with your Apple Watch

In abduction, we only know the expected value that we want to generate for our customers. We do not know the object (what) that can deliver such value. We do not know even know the working principles (how) to deliver such value.  This is pure creativity, and it starts with wondering (or guessing): How might we? (Brown, 2009). Asking this question leads to a re-framing that has the potential to actually deliver the expected value. For example, in the 1970s, while IBM was focusing on improving giant-room size computers, Apple was asking how to make the computer portable, personal, and cheaper.

Share any other examples that you might have!

And stay tuned for upcoming examples of cultural historical activity theory and their application to design thinking.

Connecting the dots of the Fourth Industrial Revolution

“Ubiquitous, mobile supercomputing. Artificially-intelligent robots. Self-driving cars. Neuro-technological brain enhancements. Genetic editing. The evidence of dramatic change is all around us and it’s happening at exponential speed. Previous industrial revolutions liberated humankind from animal power, made mass production possible and brought digital capabilities to billions of people. This Fourth Industrial Revolution is, however, fundamentally different. It is characterized by a range of new technologies that are fusing the physical, digital and biological worlds, impacting all disciplines, economies and industries, and even challenging ideas about what it means to be human.”

(via http://www.weforum.org/)

How do we remain relevant in this fast-evolving context?

Denying change is futile. Yet, the inability to understand and adapt to change is omnipresent in the economic, political, and social arenas alike, where it holds great destructive power because it represents itself through conservatism that inevitably leads to a conflict between outdated systems and institutions, as all the current events on the global scene show. In times of change, power is found in one’s ability to follow changeto adapt to change, and ultimately, to create a change, and not in the capacity to offer strong resistance or opposition to change.

I am very pleased to welcome Celina Schlieckmann (MACE16) to the BS7705 Mapping the Creative Economy class today to talk about her personal research project: “The skill sets for the new economy in the creative industries: a comparative study between Brazil and the UK”, as an effort to contextualise the challenges and opportunities of working in the creative industries nowadays and looking into the future.

Connect the dots.   . . . 

(Connect the dots between videos 1, 2 and 3 posted in our MACE Facebook group –  waiting for a discussion on those three videos and themes)