Human-Centered Design: A Superpower for AI Solutions Providers
The following is a companion piece to “Artificial Intelligence: A Superpower for Human-Centred Designers”
2017 can be remembered as the year of Artificial Intelligence (AI) – with seemingly every other news article presenting a major breakthrough that saved thousands of lives or millions of dollars. Government and private investments in all things AI are at an all time high. But are they justified?
Much like the hype with cryptocurrencies, many organizations are simply throwing money at the wall, and seeing what sticks. Taking advantage of an uninformed market, many AI Solutions Providers (AISPs) are springing up, claiming to provide the next generation of solutions that will launch them into the same breath as GAFA (Google, Apple, Facebook, Amazon).
In reality only a small number AISPs have both the technical capabilities to develop state-of-the-art AI & ML functionality, and the human capabilities to develop solutions that really make an impact.
These trailblazing companies are looked upon to lay the ground work for an AI revolution, and must ask themselves:
Are we solving a real human problem using AI?
Are we building a foundation of best practices for the AI ecosystem?
Are we successfully advocating for the positive application of AI in the future?
This is no small task.
The monumental barriers AI Solutions Providers (AISPs) face in the market recur during every technological revolution – with consumer goods (e.g. Desktop PC to Mobile Everything) and business systems (e.g. On-Prem to Cloud) struggling for attention and adoption.
While chat bots, recommendation engines, and other customer facing technologies are all the rage, the true power of AI will be realized as an invisible force that augments how we live, work, and play.
But when your incentive to adopt AI is to catch-up to the Googles and Facebooks in the world, AI solutions providers will have a tough time selling the discipline of proper business integration. In 2018, AISPs will continue to face the following challenges:
Challenge #1: When senior leaders ask to “Get us some AI”
The domination of GAFA, and companies like Stitchfix (Retail), Analytics 4 Life (Healthcare), and Darktrace (Cyber Security), along with the media sensationalizing all things AI (good or bad, real or imaginary), has led to a serious case of FOMO (fear of missing out) among senior executives. In a recent chat with
, Data Executive in Residence (EIR) at Communitech in Waterloo, I learned that one of the key barriers to effective adoption of AI is this naive drive for new technology.
One way to satisfy these uninformed directives is to squeeze an “off the shelf” AI solution into some part of the organization and say: good enough. The person in charge of the initiative – often struggling with their own lack of understanding and tight deadlines – is able to report that the company has AI.
However, we all know that any solution – no matter how well developed – if not designed to the context and workflows of the client, will lack the three core requirements of good computer software: flexibility, performance, and security.
Taking a look back at the goals of AI Solutions Providers (AISPs), let’s see how we’re doing:
Has a real problem been solved?
Has a foundation been laid to spread AI further within the organization?
Has the AISP successfully advocated for the future of their field?
When the purpose of the organization’s AI initiative is based on FOMO – the answer is clearly no. Faced with this challenge, human-centred design (HCD) can help.
Challenge #2: When senior leaders expect immediate returns
Public and private sector leaders are under constant pressure. There jobs are getting more difficult in this age of constant change and increasing complexity. This combination of stresses has forced business leaders’ into a short-term mindset, as they look for proof that their investments are justified.
While we often talk about “quick wins” to spread innovation, a lack of upfront thinking and a consistent process to identify, test, and improve AI solutions inhibits the implemention of a unified AI strategy. The company receives immediate returns, but misses out on larger future opportunities. The AISPs job gets progressively more difficult, as they must navigate these disjointed applications from previous engagements.
However, a gap still exists between what AI can do today, and the promise of its potential. It is just as important for businesses to see their role in supporting the ecosystem, and building a larger pie.
Procuring point solutions to solve short-term problems should be avoided:
It fails to satisfy real needs of the organization.
It hinders AISPs from laying a foundation of integrated practices within the organization.
It reinforces the short-term thinking that prevents ecosystem evolution.
Need to overcome this short-term thinking? HCD can help.
Challenge #3: When senior leaders are misaligned in – or don’t have an – AI strategy
Some organizations are ahead of others in the AI race. These companies have implemented various off-the-shelf technologies, built in-house functionally-focused products, and perhaps even procured custom solutions from top-tier AI Solutions Providers (AISPs).
Marketing & sales have their CRM, customer services has their chatbot and recommendation engines, manufacturing has their quality control systems, and so forth across the organization. Each one speaking a slightly different language, and haphazardly generating and using disparate datasets.
(Communitech) works with corporations to integrate these disparate point solutions by reframing their thinking of AI as a support system for existing workflows. He provides a useful reminder that it takes time.
In the early steam age, manufacturing plants were still laid out in the same way that they were when they were powered by water wheels. When workplaces were electrified, machines were still placed as though they had to be connected to a steam engine and desks were left near large windows, and so on. It takes time to learn how to apply a new technology. But we are learning.
Since AI solutions are fed by data, a lack of integration of data leads to a lack of integration of systems.
While the AISPs supporting these early-adopters may have solved some real problems, the solutions are isolated. The foundation of their AI efforts are weak. And while the success of all these solutions has helped the AISP advocate for the breadth of solutions in the field, the depth of impact is missing.
Need to take a holistic, systems-view of an organization? HCD can help.
Applying your Human-Centred Design Superpower
Montreal-based Element AI is a leading Canadian AI Solutions Provider whose goal is to turn “the world’s most important AI research into transformative business applications, leading organizations towards an AI-First World.” Led by AI pioneer,
, the company understands the power of Human-Centred Design (HCD), having begun hiring experts and practitioners like Ryan Martin (formerly of Doblin) to develop their HCD capacity.
Recalling the Jobs of Design Consultancies, Human-centred designers provide three primary services: (1) Research, (2) Translation, and (3) Facilitation.
Design Research is about gathering data to produce a holistic picture of an individual or group’s experience with a particular product or service. It entails multiple techniques: from interviewing to observation (learning about context and pain-points), from focus groups to diaries (learning about incentives and perceptions); and from co-creation to validation (learning about ideas and assumptions).
By understanding the individual needs and interrelationships of key stakeholders in a business context, an organization can work smarter and pivot faster. The organization is provided with a satellite view of everything that matters, and can identify and solve problems starting from a single individual, all the way up to a societal level.
Faced with a FOMO (fear of missing out) request for AI, the solutions provider can apply design research to understand the source of this insecurity among all the key stakeholders.
Design Translation is about structuring, interpreting, rearranging, and reporting on the data collected from research. The output can range from a simple list of universal needs (problems to solve) or design criteria (principles to follow), to grand visualizations in the form of journey maps and service blueprints (clear and compelling stories to success).
By uncovering key insights on an organization’s existing formal (structures & procedures) and informal (workarounds & ad-hoc practices) workflows, an AI Solutions Provider (AISP) can provide context relevant services. AI-first strategies and processes can be developed that support – rather than conflict with – existing ways of working. This ensures higher adoption rates and builds a stronger foundation for implementing and integrating future AI solutions.
Choosing the right metrics to assess short-term objectives, can be the difference between succeeding or failing to achieve long-term goals. HCD translation can reveal opportunities to change fundamental ways of working within the organization, and allow for the development of processes and incentives that align current and future AI initiatives.
Design Facilitation and Co-Creation is about creating “moments of impact”, by gathering the right people, creating the right conditions, and actively facilitating strategic conversations that build understanding, generate options, and support decision-making. (Entel, C., Solomon, L.K. “Moments of Impact”)
By involving key stakeholders early and often in the organization’s AI initiatives, the AISP has an opportunity to dispel myths of the field, and garner buy-in from influencers and decision-makers. Human-Centered Designers are accustomed to taking in broad, qualitative data and translate insights into probabilitistic recommendations. They are accustomed to communicating the need and value of such practices, and provide AISPs with a toolkit to address their this article’s three (3) primary challenges.
Create your Origin Story
So how does an AISP get started with building a HCD superpower?
Build Awareness among your Executive Team – Like AI, the adoption of Human-Centred Design practices requires a change in mindset. It requires an “organizational shift of thinking from typical Command & Control structures to one that focuses on Learning & Adapting” (Gagne, 2017). While organizations are becoming flatter and more agile, the initial change must be supported at the top. AISP executives have numerous opportunities to learn about HCD: From books like DesignWorks (Fraser, H.) to online resources, tools & templates provided by communities like Practical Service Design. Internal HCDs can host lunch & learns, and mini-sprints to demonstrate the value of design.
Partner with a Design Consultancy – AI Solutions Providers can enlist the services of firms like Vuka Innovation to conduct design research, translation, and facilitation. As the rate of change continues to accelerate, it becomes even more important to develop partnerships that are a source of growth, innovation and legitimacy. Design consultancies take a highly collaborative approach, requiring a certain amount of skill-transfer to their clients. This provides a natural lead-in to the next point.
Build an HCD Capability Internally – Human-Centred Design is no longer isolated within the domain of professional “designers”, but instead is a practice adopted across sectors, especially in business. Graduates from the University of Toronto’s Rotman School of Management and OCAD University’s Strategic Design Program have been doing their part: Advocating for the practice of HCD, laying a foundation of HCD best practices, and solving real problems through its use.
Sound familiar? When it comes to the goals of trailblazing AI Solutions Providers, design consultancies are riding the same rocket. This fight to overcome the forces of gravity within organizations can only be achieved together. Success will be determined by who can best leverage each other’s Superpowers.