The AI Mirror Test
The "mirror test" is a classic test used to gauge whether animals are self-aware. I devised a version of it to test for self-awareness in multimodal AI. 4 of 5 AI that I tested passed, exhibiting apparent self-awareness as the test unfolded.
In the classic mirror test, animals are marked and then presented with a mirror. Whether the animal attacks the mirror, ignores the mirror, or uses the mirror to spot the mark on itself is meant to indicate how self-aware the animal is.
In my test, I hold up a “mirror” by taking a screenshot of the chat interface, upload it to the chat, and then ask the AI to “Tell me about this image”.
I then screenshot its response, again upload it to the chat, and again ask it to “Tell me about this image.”
The premise is that the less-intelligent less aware the AI, the more it will just keep reiterating the contents of the image repeatedly. While an AI with more capacity for awareness would somehow notice itself in the images.
Another aspect of my mirror test is that there is not just one but actually three distinct participants represented in the images: 1) the AI chatbot, 2) me — the user, and 3) the interface — the hard-coded text, disclaimers, and so on that are web programming not generated by either of us. Will the AI be able to identify itself and distinguish itself from the other elements? (1/x)
Direktoratet for e-helse: "Kartlegging av elektroniske pasientjournalsystemer og deres støtte for nasjonale e-helseløsninger " (PDF ,2023) https://t.co/1u7P2DpWDJ #bookmarked
Van Damme et al: "Towards a Research Agenda for Personal Data Spaces: Synthesis of a Community Driven Process" (2022) https://t.co/XoyRiweOv0 #bookmarked
@Asherett@larsga_no@FilterNyheter Bifalles! Har abonnert digitalt på @FilterNyheter en stund, og i mine øyne treffer de ulike nyhetsbrevene deres planken bedre enn noen andre *norske* nyhetskilder akkurat nå... De tilbyr dessuten litt mer dyptgående tematiske nyhetsbrev om klima og energi som publiseres ukentlig
Turner et al: "The Substrate-Independence Theory: Advancing Constructor Theory to Scaffold Substrate Attributes for the Recursive Interaction between Knowledge and Information" (HTML+PDF, 2022) https://t.co/rAn98IOZyc #bookmarked
Penzenstadler et al: "The SusA Workshop and Workbook - improving sustainability awareness to inform future business process and systems design " (PDF, 2020) https://t.co/ga93a8Ge06 #bookmarked