AI has made massive changes to the world, particularly in food production and global governance. We exist in a world where global protests led to more democratized AI, which reduced inequities by satisfying our basic needs.
Improvements in food production, particularly in the Global South, have allowed countries to rapidly solve issues of malnutrition and hunger. This has knock-on impacts in energy production, economic development, and climate change as populations are better fed, healthier, and more resilient.
The vast majority of usage is tool AI, but replacement AI is looming as developments continue. Large tech conglomerates began the development of most AI tools, but a combination of government policy, hacktivists, and global protests democratized AI. Now, AI tools are required to be open-source within 3 years of development. This has allowed people to use the technological leaps in AI tools to great effect in their realm of choice.
There was a new global AI board called GAI formed after the unrest in the early 2030s. It helps to prevent AI safety and ethics issues while also using AI tools to supercharge solutions in places that need it. One example is that it has led to massively increased food production in the Global South. This was done by training models in diverse land use practices, but with access to millions of data points regarding soil type, plant resilience, crop rotation, and more.
After the failure to regulate technology companies developing AI, large-scale protests and strikes broke out all over the world. This led to the overthrow of some authoritarian states and most democratically elected officials being voted out. This transformation and the general unrest led to a more democratized AI ecosystem, led by experts who were able to use AI to solve problems more effectively instead of only caring about profit incentives or reinforcing power structures.
The biggest challenge this world faced was rising inequality. While not completely solved yet, there was huge progress made through global protests in the last 2020s and early 2030s. Large tech companies developing AI tools were forced to share their models and to release open-source versions to compensate for energy usage, copyright infringement, and harmful biases. Open-source models allowed groups to develop more fair, just, and ethical AI tools not as tied to profit incentives.