Difference between revisions of "356-winter-2023/final"
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=== Questioning the Premise === | === Questioning the Premise === | ||
| − | The idea of creating machines that are indistinguishable from humans can be traced back to long before Artificial Intelligence (think Mary Shelley's 1818 Frankenstein, a fiction about an artificially created, intelligent creature; recall the original Mechanical Turk—a different kind of "fiction": a human chess-master hidden within a supposed chess-playing automaton). While there may be great value in exploring the all-too-human desire for AI to mirror and outperform humans, it has so captured our cultural and technical imagination as the de facto benchmark of progress, that it is almost impossible to think of AI | + | The idea of creating machines that are indistinguishable from humans can be traced back to long before Artificial Intelligence (think Mary Shelley's 1818 Frankenstein, a fiction about an artificially created, intelligent creature; recall the original Mechanical Turk—a different kind of "fiction": a human chess-master hidden within a supposed chess-playing automaton). While there may be great value in exploring the all-too-human desire for AI to mirror and outperform humans, it has so captured our cultural and technical imagination as the de facto benchmark of progress, that it is almost impossible to think of AI as having any other overarching aims. The presumed goals are either "do what humans do and do it even better" or its commerce-friendly version: the unrelenting march towards "convenience" (and the monetization thereof). In fact, try to think of any ''other'' narrative around the overarching aims of AI in our world. Go ahead. I'll wait. |
| − | The Turing Trap is called a "trap" because of its seductive power. It has long become the holy grail in AI research, something that is rarely questioned but pursued with fervor. For example, in your experience, how much is the premise of AI research | + | The Turing Trap is called a "trap" because of its seductive power. It has long become the holy grail in AI research, something that is rarely questioned but pursued with fervor. For example, in your experience, how much is the premise of AI research called into question in other engineering contexts like courses, tech companies, and product meetings (a lot? a little? not at all?)? While there ought to be room to explore human-like machines, the peril is that this narrative would dominate the conversation, impoverish the imagination, and make uncritical nerds of us all in a staggering groupthink regarding one of the most powerful technologies of our time. |
=== Making Things to Think With === | === Making Things to Think With === | ||
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=== Specification === | === Specification === | ||
| − | * Part A: identify something you created this quarter in Music and AI that you were glad to have created | + | * Part A: identify something you created this quarter in Music and AI that you were glad to have created and that you'd like to present in the final presentations. You are welcome to polish it but chances are, if you are already happy with it, you probably don't need to do much to it |
* Part B: design or extend an interactive AI system with a '''different underlying premise''' than "more human than human" or "optimizing for convenience"; as always, deploy your system into the world in some fashion and document | * Part B: design or extend an interactive AI system with a '''different underlying premise''' than "more human than human" or "optimizing for convenience"; as always, deploy your system into the world in some fashion and document | ||
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** alternately, you may use Medium or another publishing platform (but please still link to that page from your CCRMA webpage) | ** alternately, you may use Medium or another publishing platform (but please still link to that page from your CCRMA webpage) | ||
* your webpage is to include | * your webpage is to include | ||
| − | ** a title and description of what you made ( | + | ** a title and description of what you made (feel free to link to this wiki page) |
** video recordings corresponding to your system in action | ** video recordings corresponding to your system in action | ||
** all relevant code and data files | ** all relevant code and data files | ||
** brief report on how you created these | ** brief report on how you created these | ||
** your 300-word reflection | ** your 300-word reflection | ||
| − | ** any | + | ** any acknowledgments (people, code, or other things that helped you through this) |
* submit to Canvas '''only your webpage URL''' | * submit to Canvas '''only your webpage URL''' | ||
Latest revision as of 11:15, 12 March 2023
Final Project: "Escape from the Turing Trap (or at least make a start of it)"
Music and AI (Music356/CS470) | Winter 2023 | by Ge Wang
Due Dates
- Milestone (webpage + in-class presentation): Tuesday (3/14)
- Final Deliverable (polished webpage): polished webpage due Thursday (3/23) noon
- Final Presentation (in-class presentation): Thursday (3/23) 3:30pm CCRMA Stage
The Turing Trap
First of all, thanks to Graciela for commenting on the idea of the Turing Trap in her Reading Response #2:
One idea discussed in the talk was what Dr. (Pattie) Maes called the Turing Trap: the notion that the Turing Test had fundamentally sent AI researchers down the wrong path since the very beginning of machine learning. She suggested that the Turing Test established the goal of AI research to create machines that outperformed humans. Thus, researchers are perpetually taking tasks that humans are good at (chess, driving, making art) and making models that meet and surpass our own performance. By following this path, we find ourselves optimizing against our own interests as we build systems that fundamentally aim to replace humans rather than empower humans. Instead, she proposed that we try to optimize for what people + AI would be able to accomplish rather than just AI alone. —Graciela, "Power to the People" reading response.
Questioning the Premise
The idea of creating machines that are indistinguishable from humans can be traced back to long before Artificial Intelligence (think Mary Shelley's 1818 Frankenstein, a fiction about an artificially created, intelligent creature; recall the original Mechanical Turk—a different kind of "fiction": a human chess-master hidden within a supposed chess-playing automaton). While there may be great value in exploring the all-too-human desire for AI to mirror and outperform humans, it has so captured our cultural and technical imagination as the de facto benchmark of progress, that it is almost impossible to think of AI as having any other overarching aims. The presumed goals are either "do what humans do and do it even better" or its commerce-friendly version: the unrelenting march towards "convenience" (and the monetization thereof). In fact, try to think of any other narrative around the overarching aims of AI in our world. Go ahead. I'll wait.
The Turing Trap is called a "trap" because of its seductive power. It has long become the holy grail in AI research, something that is rarely questioned but pursued with fervor. For example, in your experience, how much is the premise of AI research called into question in other engineering contexts like courses, tech companies, and product meetings (a lot? a little? not at all?)? While there ought to be room to explore human-like machines, the peril is that this narrative would dominate the conversation, impoverish the imagination, and make uncritical nerds of us all in a staggering groupthink regarding one of the most powerful technologies of our time.
Making Things to Think With
In our critical making course, we have always asked a fundamental question, "what do we (really) want from artificial intelligence?". And instead of focusing on, say, "how do we make AI more clever or more powerful", the goal of this course has always been to explore questions like "how do we want to live with AI? And through what we design with AI, how do we want to live with one another?" and ideas such as "AI as tools, not oracles". In the spirit of our critical making course on Music and AI, this final project asks you to reflect on these questions and design/extend a system to explore the idea of escaping from the Turing Trap. The truth is, of course, all of you have been doing this all along in this course, from your display of vast human creativity (especially as you grappled with the limitations of AI tools) in poetry tools, beautiful audio mosaics, and playful wekinations of the world around you.
One final project is not going to turn the tide on the Turing Trap. But here and now is as good a time to start as any.
Specification
- Part A: identify something you created this quarter in Music and AI that you were glad to have created and that you'd like to present in the final presentations. You are welcome to polish it but chances are, if you are already happy with it, you probably don't need to do much to it
- Part B: design or extend an interactive AI system with a different underlying premise than "more human than human" or "optimizing for convenience"; as always, deploy your system into the world in some fashion and document
Some possible prompts for project ideas
- extend one of your projects in this course so far or start anew!
- create a new, slightly more extensive (than in hw3) Wekinator-based system!
- design a musical instrument and perform with it!
- design a human-in-the-loop interactive tool/toy!
- a ridiculous sound-related AI contraption that no one asked for and that solves problems that don't quite exist!
- design an AI system that makes life more difficult
- remember, as always, these don't have to be useful; in fact, whimsical is good! Absurd is good! Playful is wonderful!
- tools at your disposal: anything you want to use, including all the tools so far (ChucK/ChAI, Wekinator, word2vec, mosaic) or anything else you come across
Milestone Deliverables
- a working thing that shows something of the core experience (record a video); show, don't tell!
One Final Reflection
- write ~300 words of reflection on your project. It can be about your process or the products. Tell us about your attempt to deploy them.
Final Deliverables
- create a CCRMA webpage for this etude
- the URL should live at https://ccrma.stanford.edu/~YOURUSERID/356/final or https://ccrma.stanford.edu/~YOURUSERID/470/final
- alternately, you may use Medium or another publishing platform (but please still link to that page from your CCRMA webpage)
- your webpage is to include
- a title and description of what you made (feel free to link to this wiki page)
- video recordings corresponding to your system in action
- all relevant code and data files
- brief report on how you created these
- your 300-word reflection
- any acknowledgments (people, code, or other things that helped you through this)
- submit to Canvas only your webpage URL
