- Collection:
- Georgia Law Review
- Title:
- Cheap Creativity and What It Will Do
- Creator:
- Burk, Dan L.
- Date of Original:
- 2023-07-12
- Subject:
- University of Georgia. School of Law
Law--Study and teaching
Georgia Law Review Association - Location:
- United States, Georgia, Clarke County, Athens, 33.96095, -83.37794
- Medium:
- articles
- Type:
- Text
- Format:
- application/pdf
- Description:
- Artificial intelligence (AI), in the form of machine learning systems, is becoming widely deployed across many industries to facilitate the production of new technical or expressive works. Among other applications, these technologies promise rapid product design and creation, often exceeding the capacity of human creators. Commentators and policy makers have responded to these developments with a flood of literature analyzing the ways in which AI systems might challenge our existing regimes of intellectual property. But such discussions have thus far focused on entirely the wrong questions, misunderstanding the nature of the changes that AI brings to creative development. Intellectual property is generally styled as a solution to the “appropriability” or “public goods” problem in creative and innovative production: offering a legally enhanced incentive to invest in goods that are expensive to produce, but cheap to appropriate. But cost savings from AI systems will largely occur at a different point in the production process. AI systems promise (or threaten) to lower the cost of initial development of creative goods, potentially displacing human creators. Although machine learning systems are realistically unlikely ever to provide a complete substitute for human creative inputs, their incorporation into creative production will in effect automate the generative phases of the creative development process, substantially lowering the cost of the initial stage of production. Like other cost-saving industrial automation, this can be expected to displace human labor and redefine human roles in production. The history of past automated labor displacements teaches us something of what will occur as creativity is automated. In this light, I begin to reframe the discussion of intellectual property and artificial intelligence, showing the impact machine learning will have on human creativity and innovation, and the implications these changes for intellectual property doctrine and policy. In particular, I show that cheap substitutes for human creativity will drive a shift toward forms of intellectual property that certify authenticity rather than those that incentivize production and distribution. Armed with this understanding, we can begin to address the question of how to foster human engagement in an age of synthetic creativity.
Law - External Identifiers:
- Metadata URL:
- https://digitalcommons.law.uga.edu/glr/vol57/iss4/6
- Holding Institution:
- Alexander Campbell King Law Library
- Rights:
-
