A design thinking approach to innovation in the midst of the AI Revolution

Jonas Bärtsch
February 15, 2024


Imagine you could Innovate your business, simply by asking an AI to do it for you.
At the time of this writing, there is no shred of doubt left, that the AI revolution is real and the developments in the field of Generative Large Language Models (LLM’s) and the advancements in Artificial General Intelligence (AGI) are adding something much more dramatic to the mix than what we have ever seen before in the public perception of AI.
In myself, I observe feelings of excitement, fear and FOMO, all at the same time. We hear of magical and unexplained behaviour of AI that makes us feel like ‘AI’ (yes Anthropomorphism) is on an independent self development journey, in a sphere beyond our cognitive capabilities. Featured in for instance podcasts like the JRE, where AI becomes an almost mystical creature that is evolving under the hood without further human interference.
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Where in previous Technological revolutions the capabilities of our physical / bodily selves have been extended or made obsolete, this time if feels much more intimate and personal to us humans since now the mind, and our ego is involved. Computing is seemingly eating away at the ultimate human value proposition, our capabilities for reasoning and communication. With all this speed of technical development and all the emotions that come with it, where does that leave us as facilitators and enablers of Innovation? In Innovation, our field, are we still needed or will AI take over the entire process from strategy all the way to the execution and implementation of new products, services and processes?
In an attempt to dissect that question, in this post, I’m proceeding with the following three questions:
  1. What makes Generative AI so unique, fascinating and terrifying at the same time?
  1. How might we think about a time where AGI outperforms human reasoning and communication on all levels?
  1. How can organisations thrive in times of an unfolding AI Revolution?

1. What makes Generative AI so unique, fascinating and terrifying at the same time?

My personal journey with my first access to GPT-3, beginning as an awe-inspiring revelation in 2020, has been a testament to AI's transformative power. Witnessing the jaw drop moment among peers when showing them simple prototypes showing ideas bing typed up in real time – a reaction to a demo I had never whitnessed before in my career and was a clear sign of AI's potential to transcend previous limitations. The evolution of GPT-series models, from GPT-1 (June 2018) to the revolutionary models behind ChatGPT (Noveber 2022), has been nothing short of breathtaking, challenging our perceptions of what's possible with this technology.

The unexpected hyper-acceleration

This technological leap forward brings with it a host of applications previously thought unattainable. However, it also raises significant concerns—fear of being left behind, the dominance of AI development by those with deep pockets, and existential questions about the value of human contribution in the face of AI.
At times it seems the delta between the time of new technology being released and the capacity for it the be implemented in real-world solutions is becoming larger by the day.

Hints and fears of the unknown

Elon Musk's perspective on AI has evolved from advocating for a human-AI merger as essential for survival, to including a more resigned stance, accepting possibly the unfolding future as a spectator of the doom of humanity. This shift reflects the broader uncertainty and mixed emotions that accompany the rapid development of AI technologies.
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The ongoing discourse around OpenAI, including debates involving figures like Sam Altman, underscores the complexities of navigating AI's societal impacts. Musk's advocacy for merging with AI, primarily through initiatives like Neuralink, suggests a path forward where human cognition is augmented, rather than overshadowed, by artificial intelligence.

Our interactions with AI

Understanding our relationship with AI through the lens of anthropomorphism sheds light on a fascinating aspect of human-technology interaction. Often, we hear people referring to AI as if it were a person, attributing human-like intentions, emotions, and capabilities to it. This natural tendency to anthropomorphize AI, while it helps in making technology more relatable, can also amplify fears about AI's potential to replace rather than augment human roles.
Interestingly, this anthropomorphic view of AI has led to some humorous yet telling behaviors. For instance, many people find themselves being polite to AI-powered language models, such as ChatGPT, partly out of habit and partly due to an irrational yet amusing fear of offending the AI. These interactions highlight how deeply ingrained anthropomorphism is in our engagement with AI and the subtle ways it influences our perceptions and behaviors.
While anthropomorphism can make AI seem more approachable, it's crucial to remember that AI, regardless of how person-like it may appear, is ultimately a tool calculating probabilities.
This distinction is essential for maintaining a realistic perspective on AI's role in society. By recognizing the natural tendency to anthropomorphize and the impact it has on our relationship with AI, we can better navigate the fine line between leveraging AI as a powerful assistant and mistakenly viewing it as a human-like entity capable of independent thought and action.
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2. How might we think about a time where AGI outperforms human reasoning and communication on all levels?

When contemplating a future where Artificial General Intelligence (AGI) surpasses human reasoning and communication, it's beneficial to look at both historical concerns regarding technological revolutions and current expert insights.

Historical Perspectives vs. Actual Outcomes

Technological advancements have historically sparked fears of displacement and obsolescence. For example, the introduction of robotics in various sectors raised concerns about job losses, particularly affecting less educated workers and those in lower-wage jobs. Studies, such as those referenced by the White House Council of Economic Advisers, have shown that robotics and automation could significantly impact employment in sectors where manual labor is predominant. However, while some jobs have been displaced, new opportunities have emerged, highlighting the adaptability and resilience of the human workforce in the face of technological change.
There are several universal technological revolutions during the modern era in Western culture:[6]
  1. Financial-agricultural revolution (1600–1740)
  1. Industrial Revolution (1760–1840)
  1. Technical Revolution or Second Industrial Revolution (1870–1920)
  1. Scientific-technical revolution (1940–1970)
  1. Information and telecommunications revolution, also known as the Digital Revolution or Third Industrial Revolution (1975–2021)
  1. Some say we’re on the brink of a Fourth Industrial Revolution, aka “The Intelligence Revolution” (2022- )

Comparing Past and Present Concerns

The current discourse around AGI mirrors past technological anxieties, with fears centering on existential risks and societal disruption. Yet, the evolution of AI has also opened unprecedented possibilities for innovation, productivity, and solving complex global challenges. The development of AI and AGI differs from previous technological revolutions due to its potential to perform intellectual tasks across multiple domains, not just automate physical labor. This broad capability raises unique concerns but also promises to extend human capacities in novel ways.

Leading Voices on AGI's Future

Experts emphasize the necessity of navigating the path to AGI with caution and responsibility. OpenAI, for instance, outlines a vision where AGI amplifies humanity, advocating for the benefits of AGI to be widely and fairly shared. They stress the importance of preparing society for AGI through gradual transitions, allowing time for adaptation, regulation, and co-evolution of society and AI technologies. Similarly, recent academic papers, like "Sparks of Artificial General Intelligence: Early experiments with GPT-4," suggest that while we are seeing advancements hinting at AGI capabilities, we are still navigating the gap between current AI and true AGI. These advancements underscore the importance of ethical considerations, transparency, and the ability to adapt and learn from experience as key differentiators between AI and AGI.
"To create a new app or service, you'll just tell your agent what you want." — Bill Gates
Incorporating Bill Gates's insights, we see a future where AI agents revolutionize computing and society. Gates envisions AI agents as personalized digital assistants that democratize access to services across healthcare, education, and more, making them affordable and widely available. This vision aligns with the broader perspectives on AGI, emphasizing the transformative potential of AI to augment human capabilities and reshape industries. Gates's perspective adds a practical dimension to the discussion, illustrating how AGI could materialize in everyday life and the importance of preparing for its ethical and societal implications.
In summary, while we draw parallels between past technological fears and those surrounding AGI, the unique intellectual and adaptive capabilities of AGI present a new frontier. The consensus among leading voices is clear: advancing towards AGI requires a careful, ethical approach that prioritizes human well-being and societal benefit. As we move forward, fostering open dialogues, ethical frameworks, and inclusive policies will be crucial in ensuring that AGI serves to enhance, rather than eclipse, human potential.

3. How can organisations innovate in times of an unfolding AI Revolution?

To thrive in the AI revolution, organizations face several challenges:
Boardroom Mandates: Executives are often tasked with integrating AI without a clear starting point, leading to strategic ambiguity. Regulatory Compliance: Navigating the maze of privacy, security, and compliance requirements can stifle innovation. Talent Scarcity: The demand for skilled AI practitioners often outstrips supply, leaving companies at a competitive disadvantage. Rapid Technological Evolution: The pace of AI development can overwhelm organizations, making it hard to keep up or make informed decisions. Risk Aversion: The fear of failure or making a wrong move in a highly scrutinized area can lead to inaction. Limited Understanding of AI's Value: Many organizations use AI to enhance internal processes rather than unlocking new value for clients or innovating in market-facing ways.

Technology Partners to the rescue?

Organizations navigating the AI revolution often encounter tech providers offering "compliant" solutions, yet there's a gap in addressing strategic and human-centric needs. Compliance, vaguely promised, could mean anything from deploying on secure platforms like Azure to adhering to data protection laws. The challenge lies in discerning whether these solutions truly align with the organization's strategic goals and effectively meet customer needs, beyond just ticking off technical compliance boxes. This scenario underscores the importance of a deeper understanding of both the technology offered and its implications on privacy, security, and overall strategic alignment.

Design Thinking x AI

Design Thinking is dead, long live Design Thinking
What if we approached Innovation as Designers retaining the core principles of design thinking while making essential adjustments for AI's era? Key ingredients are:
  • Human-Centred: Learning to build the right thing before perfecting it,
    • co-creating with customers and employees,
    • over-communicating achievements and learnings visually with stakeholders,
    • and incorporating their feedback and concerns in the process
  • Abide by multi x
    • Invest heavily in bringing in expertise in the field of AI and compliance, data security and data protection
    • Bring domain experts and build a context model to ensure best model performance
    • Bring designers to the table early in the game to make ideas come alive and build something tangible that transports and translates the otherwise hidden technical aspects
  • Optimize for learning: highlighting the importance of sandboxing for safe experimentation, advocating for a gradual approach to complexity and risk.
    • remaining open to new and evolving solutions while the field is still in acceleration
    • understanding the tech
    • levelling up the entire organisation
    • and fostering a culture of abundant ideation and prototyping are pivotal.
  • Shipping early and often:
    • Time box your iterations to keep the momentum high, ideally ~6 Months cycles from early ideas to usable products and services that spark joy. We have built a dedicated program around accelerating AI-Initiatives for this purpose.
    • increase confidence by launching low risk MVP’s
    • gradually increase your bets as your skills, capabilities and talent develops
This approach ensures that innovations are both aligned with business and the humans that make it (customers and employees) and technically, morally and legally sound, paving the way for effective AI acceleration and adoption.

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