John Smart’s “four futures” adaptation of Dator’s futures cone is a framework that explores four potential future scenarios based on the intersection of two axes: the axis of naturalness (from “stewardship” to “transcendence”) and the axis of self-interest (from “growth” to “constraint”).

1. Stewardship and Growth: In this scenario, the focus is on sustainable development and responsible resource management. Examples could include efforts to promote renewable energy sources, conservation initiatives, and the adoption of environmentally friendly technologies. One example from recent history might be the global shift towards renewable energy and the increasing adoption of electric vehicles.
2. Stewardship and Constraint: This scenario emphasizes the importance of preserving natural ecosystems and limiting human impact on the environment. Efforts in this direction might include stricter environmental regulations, the protection of biodiversity, and the establishment of protected areas. An example from recent history could be the international efforts to combat climate change, such as the Paris Agreement signed in 2015.
3. Transcendence and Growth: In this scenario, technological advancements play a central role in shaping the future. Examples might include breakthroughs in fields like artificial intelligence, biotechnology, or space exploration. From recent history, one could point to the rapid development and deployment of AI technologies across various sectors, including healthcare, transportation, and finance.
4. Transcendence and Constraint: This scenario explores futures where human society transcends its current limitations while also facing significant constraints. Possible examples could involve scenarios where global challenges, such as resource scarcity or social inequality, drive the need for radical societal transformations. However, specific recent historical examples fitting this scenario would require analysis beyond my knowledge cutoff.

It’s important to note that these examples are interpretations based on the general concepts of Smart’s framework. The actual realization of these scenarios is complex and depends on various factors, including social, political, and technological developments.

Example 1:

Electric vehicles: 6 milestones that may help full adoption of EVs

https://techaeris.com/2024/03/15/evs-electric-vehicles-milestones-adoption/

Example 2:

Cost Of Climate Change: Why Saving Our Planet Now Is Cheaper

https://www.forbes.com/sites/nilsrokke/2024/03/20/cost-of-climate-change-why-saving-our-planet-now-is-cheaper/?sh=5803e30979ee

Example 3

Unleashing AI’s Upside: A Blueprint For Workforce Transformation

https://www.forbes.com/sites/forbesbusinesscouncil/2024/03/19/unleashing-ais-upside-a-blueprint-for-workforce-transformation/?sh=168596477c67

Example 4:

Mega trends: Climate Change and Resource Scarcity

https://money.usnews.com/investing/articles/megatrends-climate-change-and-resource-scarcity

Apparently the answer is to explore what companies drive AI innovation because ultimately it’s going to be advantageous to use AI to generate new ideas from the input we give it. Electricity, Graphics Cards, Datacenters, Etc. are the new markets. This is the jam!

I need copious amounts of electricity for AI and my electric cars! To rob one for the other is like corn prices spiking, causing tortillas prices to spike and people not being able to afford traditional food, because of the demand for E85 ethanol production.

The radical solution is going to be a compromise that we’re willing to accept, as long as all the parties agree. Since it’s people, compromise is at the risk of personalities not clashing. However if the NLP engineered AI produced an answer from a quantum computer… we’d probably accept it.

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