It is intelligence that was artificially made.
It is intelligence, artificially constructed.
The two sentences seem to only change the order of interpretation, but in fact they carry very different meanings.
The first sentence makes you focus on the technology,
and the second makes you focus on the human.
Right here is the background for how the keyword "humanities" or "liberal arts" entered the AI conversation.
Right here, some people call it wordplay or a cloud-in-the-sky talk. That is unfortunate.
For web services before 2010, most PMs had a developer background. About two or three years later, most PMs in the field began to come from the planning side. It was probably because features and services are different genres. In 2020, most PMs or companies doing AI-related services are developer-based. So for now, interpretations of AI are still sometimes dismissed as cloud-talk. Around 2023 or so, as service-related people finish their learning and understanding, I expect many changes in general organizations and services. Of course, the PMs or POs at that point will not come from today's development or planning departments. Experience or familiarity tends to become a weakness during periods of change. Just as the traditional web-planning PMs were gradually replaced one by one by people who majored in HCI, cognitive psychology, or service design, I expect AI-based services will also be taken over by a new discipline. (For reference, the former traditional web-planning PMs (Project Manager) are flowing toward SI work such as infrastructure, systems, and solutions, while a new generation of HCI or service-design majors is becoming the backbone of B2C-based service PMs (Product Manager or PO).)
New technologies are made by technologists, but assigning usefulness to that technology is a different genre. AI-related services (prediction, chatbots, AR/VR, cloud, etc.) still feel very rough. AI is a genre that shines most when it does not reveal itself. Isn't human intelligence the same?
Competition over technical specs is only at the level of PDAs. To survive in the market after leaving school or the lab (dev cave), you need to think hard about services that give the technology its usefulness.
