Focus on automating human labour as much as possible. Problems in the world all trace back to lack of resources. A rich man can afford to be 'nice to the environment', a poor man can't.
The below all are easier machine learning problems than self-driving cars, yet no big tech companies or national initiatives are focused on aggressively applying machine learning to them.
Likely a couple of billion dollars, a year, and a 100 people lab would 'solve' each specific problem.
1. Robot that cooks meals, and clean the dishes afterwards. That saves billions of hours daily.
2. Robotic self-cleaning toilets. Saves another billion hours daily.
3. Robots that can dig up dirt and build a house from that dirt.
4. An app that can teach anyone anything like a teacher would - literally - a talking avatar and cameras and voice output and machine learning powered dialogue.
5. Home manufacturing 'box' that can make 95% of anything that anyone typically wants (some arrangment of 3d printer/laser cutters/pcb placement/wood router machines etc, that can take plastics/wood/metal/electronic components and output a gadget/furniture etc)
The above 5 give the equivalent of a 'basic income' for everyone (if distributed to everyone, and assuming the finished gadget is about the size and complexity of an automobile).
Then the inputs/ouputs problem of energy/raw materials/waste needs to be provided.
Disregarding scientific advances like fusion power etc (which require more than 100 billion maybe, or not possible), a drone distrubution platform for getting the energy / matter (input/waste) handled.
To do this (as above, 100 people, a year, 1 billion dollars)
6. p2p aerial surveillance system for air traffic managment of millins of drones. Basically, a sky pointing camera gadget that analyzes and broadcasts what it sees and process. Millions/billions of these camera gadgets airdropped every few 100 meters .
7. a drone that can carry 100 kilos and drop ship materails/waste p2p using the p2p air traffic control. The drones are battery operated with range a coupel of kilometers.
8. a drone that can mid-air 'refuel' the above drones. Basically a flying battery that recharges that larger cargo drones.
Summary - 'gadgetize' every problem (it becomes a self contained mechano-electrical desktop/fridge size thing that a team of 100 people can rapidly iterate on) and throw machine learning at it at heavily as possible. Seek to eliminate human labour as fast as possible.