Reframe: Players within innovation

Adding pop culture implications to innovation concepts

Feb 03, 2025

Written 2023. Published to SubStack 2025
The ask was to consider a podcast and an innovation theory. I added the other elements.

When Stan Lee created Tony Stark/Iron man, it was a personal challenge to make an unlikable character, likeable. He created Stark as a highly skilled, billionaire weapons dealer. However, under academic scrutiny, you may discover pop culture implications to the character against the backdrop of the Cold War and industrialisation. Stan Lee reframed the archetype of the entrepreneur and redirected attention away from the military and state as an innovation source. These pop culture changes may have framed perceptions for youth and for future generations. Is an update in order?

In 2023, I wrote this piece and used it to explore the State is a risk taker in innovation. When I did, I drew from Mariana Mazzucato’s book, The Entrepreneurial state (2018) and EconTalk’s podcast, Annie Duke on the Power of Quitting.

Before we get into the podcast, I want to side track…
Let’s consider game theory and AlphaGo. Game theory emerged as a branch of applied mathematics to solve problems in economics. The studies in this field resulted in economics being compared to a game and “a solution to a game describes the optimal decisions of the players, who may have similar, opposed, or mixed interests, and the outcomes that may result from these decisions” (Davis, 2022).
Now consider AI. What could happen if we would consider artificial intelligence (AI) a player within innovation and strategy? Lets use AlphaGo as an example. In 2015, AlphaGo was the first computer program to defeat a human professional Go player (AlphaGo, n.d). Go is a board game considered to be complex, in part, due to the possible board configurations. It requires each opponent to strategically create territories and capture the opponent's stones. During the AlphaGo documentary (AlphaGo, 1:19:00), we are introduced to the concept of slack moves; moves described as lazy because of an understanding that better moves could have been played in that turn. This strategy has challenged the mode of thinking in which “we have been using score as a proxy for the chance of winning” (AlphaGo, 1:18:00). AlphaGo appeared to use a strategy to win without overcapitalising.

Ok, so now with the pop culture references and introductory overview behind us, I turn to the interesting work of Mazzucato (2018) who argued that a State is capable of generating innovation to support economic growth. She provides research detailing how the State functions as a source/contributor of innovation and outlines that private companies absorb these insights to develop commercial goods for profit generation that stay in private sectors. Mazzucato believes “the more we talk down the state’s role in the economy, the less able we are to up its game and make it a relevant player”. As a result, there maybe perceptions that the State is not capable of attracting top talent or picking winning new innovation/economic sectors. Her findings point to the State making large contributions to the research component in innovation development. The business cases she draws from include early research and development into the internet, semi-conductors, pharmaceutical-biotech and the iPhone. She draws borders on the economic game board in terms of where innovation originates and her research claims the State is a player in high risk, high capital economic ecosystem.

Hold on. I just need one more paragraph to talk about her work. She explains that these business cases form “the case for a targeted, proactive, entrepreneurial State, one able to take risks and create a highly networked system of actors”. These actors would include private sector’s entrepreneurs and enterprises and should be coordinated over the medium to long-term. She highlights the need for balance in the networked ecosystem using the symbiotic versus parasitic innovation ecosystems concept. It is used to relate the possibility of one player, for example public or private, benefiting more from an innovation. This implies that all rewards may go to one side despite risk being present within the ecosystem as a whole. It relates to an awareness that one player could avoid returning any earnings or trigger the crowding out effect. Specific to the crowding out effect, she highlights that there is a risk that the State “invest in areas that the private sector would not invest in even if it had the resources. And it is the courageous risk-taking visionary role of the State that has been ignored”.

Lets loop in EconTalk podcast’s, Annie Duke on the Power of Quitting. The podcast is hosted by American economist, Russ Roberts. His guest was Annie Duke, a former professional poker player, decision strategist and author of Quit. During the podcast, Duke shares insight into decision and resource utilisation strategies in terms of forager ant behaviour (16:59) and the monkeys and the pedestals mental model(1:04:04). The forager ant strategy exemplifies an approach to simultaneously exploring and exploiting (food) resources. The monkeys and the pedestals mental model is explained as a thought experiment when about to make a decision under uncertainty. The thought experiment asks one to;

Imagine you had to train monkeys to juggle flaming torches while also standing on a pedestal. Then identify which part of the project to start with, building the pedestal or training the monkey. Which if you are investing in a project, the monkeys represent the uncertainties.

Remember the ask when writing this piece was to consider a podcast and an innovation theory. How could the ant strategy and mental model thought experiment intersect Mazzucato’s work?
The idea of an entrepreneurial State highlights the importance of enabling smart and inclusive growth through the identification of all players that contribute to economic growth. The ants strategy, in the context of economic growth, asks us to consider organising players into an inclusive structure. By simultaneously having some players explore or exploit it may be possible to effectively influence resource and capital utilisation. The monkeys on pedestals concept (1:04:04) exemplifies a smart tool that supports (1) surfacing critical information to support decision-making under uncertainty, (2) identifying where to direct resources/stakeholders to obtain critical learning and defining project progress (3) understanding when to quit due to any false progress, independent of initial capital/labour investment. These last 2 points are valid for deeper reflection under the quit or grit discussion from the podcast.

Where is all of this going?

In terms of technology, let us recall AlphaGo and the slack moves strategy. Within game theory, there could be something of interest for economic players to pay attention to as both the technology and its use cases develop. What we initially learnt was that AlphaGo’s strategy was discussed as a win using a different paradigm. AlphaGo did not expend resources and overcapitalise. To win, it seemed not to over invest and seize territory that it did not need. How could this impact players in an ecosystem. Could the entrepreneur and State consider reorganising its roles and rewards structure? In the future, would we see economic focused AI supporting economic players in strategy development? I could only speculate. If so, I would argue that it would be important to understand these models and the values it may have inherited/developed from its training.

In terms of Mazzucato’s Entrepreneurial State, we could get a sense that the State is perhaps being dealt a bad hand. Filtered through an academic lens of Adler et al. (2009), could one draw from the concept of ambidexterity. What could the economic gameboard look like if players explored and exploited as a coordinated strategy? How would players pair up? Could we frame and reconsider State/start-ups, State/enterprise and start-ups/enterprise as working together as ambidextrous subunits. Could these relationships seek to treat the incremental knowledge gained as shareable, available for development by the next subunit. Could this resolve tensions of needing to find a winner? This strategy possibly reframes the crowding out claims noted in the book, in that an ambidextrous relationship could also define roles/rules in the ecosystem. The role of the State in innovation, according to Mazzucato, is that of driving radical innovations in early stages. In this approach, could each work with an understanding of defined project progress and knowing when it's the next player's turn.
The other implication is that public money is laying the groundwork for what the private sector later commercialises and profits from. Reviewing the analysis, one could be inclined to agree with Mazzucato on a need for a strategy that seeks to implement rules/policies under a framework designed to recoup rewards. Mazzucato believes there is an “inability of the State to argue its own position, to explain its role in the winners that have been picked […]”. She claims that there is a lack of understanding by the State of how its own investments have contributed to the emergence of successful companies. If this information was better understood it would be possible to defend accusations of failures to support or drive innovation.

There needs to be a reframing of risk, role players and perhaps also the role of the entrepreneur in society. A winner takes all mentality should not be normalised as the only strategy. Entrepreneurs, business and the state should consider the roles they play in driving innovation. As for AI. Its early days. Depending on its development and the companies driving this, it is too early to say if it could support the development of any collaborative strategies that could benefit humanity. What do you think, share your thoughts below ;)

Reframe: Players within innovation

Adding pop culture implications to innovation concepts

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