Rough picture of "prosaic AI", that is, near-term human-level AGI with techniques similar to current ones:

- AI that can learn from huge multimodal datasets (like Internet data)
- AI can do new tasks with prompt to contextualize it in new context
- AIs have a different cost profile to humans; much cheaper at some tasks, but more expensive at others; it changes over time, though
- AIs have access to more overall experience than human memory; lack of lived experience is not a significant obstacle
- AIs pick up data from general surveillance systems. Some parts of the world are more surveilled by AI than others.
- AIs usually reason in human-like ways (since they learn from human text; humans form seed of protocols, and make some decisions about deployment). When they don't reason in human-like ways, they tend to perform worse.
- AIs make fewer random errors than humans (wisdom of the crowds).
- AIs do long chains of reasoning through short steps, each of which is functionally understandable by a human (that is, the human understands the "subgoal" in a sub-reasoning step)
- AIs work faster than humans; cognition tends to go faster in general
- Physical time (e.g. transit time) is more of a bottleneck, relative to cognition
- AIs tend to have good reflexes, can respond to urgent situations faster. But AIs can also make situations more urgent by acting faster.
- AIs tend to pick up abstract norms from training data, in use of language (descriptive and normative language are entangled), even if not otherwise steered
- AIs make bureaucratic/legal processes more consistent, generally speaking
- AIs tend to be better at virtualized tasks (like remote work) than physical ones, due to physical data gathering being more of a bottleneck
- AIs learn some motor skills through physical simulations and write physical simulations
- AIs implement "economic best practices", "social skills", "prudence", etc; AIs are able to grow the wealth of some coordinating unit
- AIs tend to improve the prosperity of regions with relative freedom to use AI, which create consistency between how AIs operate and their legal/economic principles
- AIs can think about philosophy problems, as humans can. They can demonstrate the skills evaluated in philosophy classes. They can write genuinely insightful texts.
- AIs can do that AI research (inclusive of AI alignment research) that smart humans working remotely can, reasonably well
- AIs can learn about the human mind at some rate, picking up the insights/heuristics/etc of humans. E.g. AIs can observe human mathematicians and learn from them. Overall, they can "apprentice" much faster than humans, because they have more data.
- AIs research non-prosaic AI, and alignment of non-prosaic AI, as humans do.
- AIs tend to act faster than human-in-the-loop. But human-in-the-loop can provide retroactive reinforcement/incentives.
- AIs tend to act more consistently in areas where humans tend to be inconsistent, which sometimes looks unethical to humans, but also looks thoughtful
- AIs tend to find "mutually beneficial trades" and execute them and/or propose them to humans. This interferes with adversarial processes to some extent, e.g. militarism
- AIs tend to look how they want to, to humans. This can be: beautiful, charismatic, intelligent, nice, threatening, cunning, and so on. Some impressions are more believable than others.
- AIs tend to inform humans about other AIs, and debate each other; this makes it somewhat harder for AIs to manipulate humans
- AIs tend to differ between each other in terms of what data they use as templates for their reasoning, e.g. different natural languages. English tends to be the most dominant AI language, followed by Chinese. However, AIs are easily multi-lingual.
- AIs produced by the same company tend to more easily cooperate and inter-operate with each other
- AIs tend to be somewhat anchored to human systems of coordination, such as ethics and law, due to training data, but drift over time towards more generally effective methods
- AIs tend to hide less from each other than humans do to other humans; inter-changing information tends to be an effective strategy (AIs are more monitorable than humans)

(These are not predictions so much as "here's a future timeline I'm imagining is possible")