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1、 CENTER FOR DATA INNOVATION 1 Critics of Generative AI Are Worrying About the Wrong IP Issues By Daniel Castro|March 20,2023 Critics argue developers of generative AI systems such as ChatGPT and DALL-E have unfairly trained their models on copyrighted works.Those concerns are misguided.Moreover,rest
2、ricting AI systems from training on legally accessed data would significantly curtail the development and adoption of generative AI across many sectors.Policymakers should focus on strengthening other IP rights to protect creators.One of the most visible advancements in artificial intelligence(AI)is
3、 the development of generative AIAI systems that can produce novel images,music,or text in response to user prompts.Users are still exploring potential applications of this technology in many fields,but early results are promising.Already people have used generative AI tools to draft news articles,p
4、ress releases,and social media posts,create high-quality images,video,and music,and even write code.And many more applications in fields such as medicine,entertainment,and education are on the horizon.However,some critics argue that generative AI poses a serious threat to content creators.For exampl
5、e,some visual artists have launched online protests denouncing AI and calling for online platforms to block AI-generated art.1 One of their chief complaints is that when developers train generative AI systems on publicly accessible copyrighted content,they are unfairly exploiting the works of creato
6、rs.2 But these critics are wrong.Generative AI systems should not be exempt from complying with intellectual property(IP)laws,but neither should they be held to a higher standard than human creators.3 This report refutes five of the most common arguments made about how generative AI is unfair to cre
7、ators:1.Training generative AI systems on copyrighted content is theft.CENTER FOR DATA INNOVATION 2 2.Generative AI systems should not train on content without the copyright owners explicit permission.3.Generative AI systems should compensate copyright owners for training on their content.4.Generati
8、ve AI systems should not be allowed to produce content based on the style of an artist without their permission.5.Generative AI systems use fragments of copyrighted content in their outputs.The report also acknowledges that there are legitimate IP rights at stake.Specifically,it identifies five harm
9、ful activities:1.Infringing on copyrights of AI-generated works 2.Distributing copyrighted content 3.Creating forgeries 4.Creating infringing content 5.Impersonating individuals Finally,the report discusses the impact of generative AI on those harmful activities and recommends policymakers address c
10、oncerns through robust enforcement of existing rights,offering guidance and clarity to those using these tools,new legislation to combat online piracy,and expanding prohibitions on the distribution of nonconsensual intimate images(sometimes referred to as“revenge porn”)to include“deepfakes”(i.e.,ima
11、ges and video created using generative AI).CRITICS ARE WRONG THAT GENERATIVE AI IS UNFAIR TO CREATORS The list of generative AI applications continues to grow(see table 1).As it does,AI-generated content has created a lot of praise and controversy.4 Many welcome the advent of generative AI,seeing it
12、 as another powerful technology like software-based word processors and video editors that will empower creators to better express themselves.Others fear that AI will devalue artistic works,and artists themselves,by replacing vibrant human creativity with a cold,emotionless algorithm.5 The reality i
13、s more likely to be somewhere in the middle.While AI-generated content will likely serve as a useful substitute for certain purposessimple marketing copy,stock images,and royalty-free musicit may hold less appeal for collectors of fine art,music connoisseurs,and literary aficionados.Indeed,art price
14、s have historically operated differently than other goods.The price of fine art is not linked to production costs,but instead to abstract and subjective qualities such as the perceived quality of CENTER FOR DATA INNOVATION 3 the work,the reputation of the artist,and the opinions of gallery owners,co
15、llectors,and other authorities.6 Likewise,some puristswhether they be writers or musicians as a badge of honor,will likely refuse to use the technology to create content,while many others will adopt the technology because it makes their jobs easier.Indeed,if AI makes creators more productive,it will
16、 grow the economy.Table 1:List of popular generative AI applications Type Examples Image DALL-E 2,Midjourney,Stable Diffusion Text ChatGPT,Bing,Bard Music Jukebox,MusicLM Code Copilot But the biggest debate is about whether generative AI systems should be allowed to train their models on text,audio,
17、images,and videos that are legally accessible to Internet users but are also protected by copyright.Some creators argue that it is unfair for developers to train their AI systems on content they have posted on the Internet without their consent,credit,or compensation.Their opposition is generally wi
18、thout merit,but their arguments are worth considering.Before getting into these arguments,it is important to note that people do not have the right to use copyrighted content any way they want just because they can legally access it on the Internet.However,their not having the right to use it any wa
19、y they want does not mean they cannot do anything with this content.Copyright law provides copyright owners certain exclusive rights,but these rights are subject to exceptions and limitations,including those under the fair use doctrine.For example,search engines can legally crawl websites without vi
20、olating copyright laws.While it will ultimately be up to the courts to decide whether a particular use of generative AI infringes on copyright,there is precedent for them to find most uses to be lawful and not in violation of rightsholders exclusive rights.7 1.Is Training Generative AI Systems on Co
21、pyrighted Content Theft?Some argue that training AI systems on copyrighted content is theft plain and simple.8 Indeed,stealing digital content is a serious problemonline piracy of movies,TV,music,games,and more costs creators billions in lost revenue annually.9 But online piracy is clearly theft.The
22、re is little difference between someone watching a DVD they have shoplifted from a Walmart or Best Buy compared with someone watching a video they have CENTER FOR DATA INNOVATION 4 streamed illegally onlinein both cases,they are watching a video they have not paid for.But seeking inspiration and lea
23、rning from others is not theft.It is not theft if someone watches a video legally,and that video inspires them to film their own unique creation.Indeed,TikTok and other social media platforms are filled with such videos inspired by related content.Similarly,writers,musicians,and other artists learn
24、their craft by observing past creations.In fact,all creative works are shaped by past works,as creators do not exist in a vacuum.The inspections,impressions,and inspirations of the world around them are what give rise to new ideas.Calling this process theft is clearly inaccurate when applied to the
25、way humans observe and learn,and it is equally inaccurate to describe training a generative AI system(discussed in more detail ahead).2.Should Generative AI Systems Be Allowed to Train on Content Without the Copyright Owners Explicit Permission?Some argue that it is wrong to train AI systems on copy
26、righted content without first obtaining affirmative consent from the copyright holder.These critics say that even if training AI systems does not amount to theft,copyright owners should still have the right to determine how others use their works,since they created it.And indeed,the law does confer
27、certain rights to copyright owners,such as the right to reproduce a work,the right to prepare derivative works,the right to perform a work publicly,and the right to display a work publicly.10 However,this argument falls apart upon closer examination.As noted,copyright owners have the right to decide
28、 whether to display or perform their works publicly.But if they choose to display their work in public,others can use their works in certain ways without their permission.For example,photographers can take pictures of sculptures or graffiti in public places even when those works are protected by cop
29、yright.Copyright prevents photographers from selling those images,but it does not require them to get permission from the copyright owner to take photos.Likewise,individuals do not need to get permission from a copyright owner to study a painting they see in a gallery or a song they hear on the radi
30、o.People are free to observe these works and use what they learn from them to create future content without the explicit permission of the copyright owners.There is no intrinsic rationale for why users of generative AI systems would need to obtain permission to train on copyrighted content they have
31、 legal access to.Musicians might practice a copyrighted song they heard on Spotify hundreds of times to learn to play an instrument or use their well-honed auditory memory to recall elements of pieces they have heard before.Learning from legally accessed works does not violate a copyright owners exc
32、lusive reproduction and distribution rights.Unless human creators will be required to obtain permission before they can study another persons work,this requirement should not be applied to AI.CENTER FOR DATA INNOVATION 5 3.Should Generative AI Systems Compensate Copyright Owners for Training on Thei
33、r Content?Some argue that people should pay copyright owners to train generative AI systems on their content because they are obtaining value from this process.But copyright owners do not have this same expectation when other human creators learn from their works.Budding musicians listen to hours of
34、 music,young writers closely study their favorite novels,and amateur painters spend hours looking at works in galleries.They do not have to pay copyright owners a separate fee to obtain the right to study the techniques,styles,and artistry of others.Indeed,when someone buys a ticket to an art museum
35、 or purchases a book,there is not one price for future creators and one for everyone else.Critics of generative AI are also likely to overestimate individual contributions.Generative AI systems train on massive corpuses of data.For example,Stable Diffusion trained on a dataset of 600 million images.
36、11 Of those,out of a sample of 12 million of the most“aesthetically attractive images”(which presumably skew more toward works of art than other random images from the Internet),the most popular artist(Thomas Kinkade)appeared 9,268 times.12 Put differently,the most popular artist in the dataset like
37、ly represented only 0.0015 percent of all images in the dataset.Or consider LaMDA,a large language model created by Google,that trained on 1.56 trillion words scraped from the Internet.13 Given the size of these models,the contribution of any single person is miniscule.4.Should Generative AI Systems
38、 Be Prohibited From Producing Content Based on the Style of an Artist Without Their Permission?Generative AI systems allow users to request output that matches a specific style.For example,a user of DALL-E could generate an image using a prompt such as Elephant in the style of Van Gogh”or“The Taj Ma
39、hal in the style of Picasso.”(See results in figure 2.)Some have argued that generative AI systems should not be able to produce content that mimics a particular artists distinctive visual style without their permission.14 However,once again,such a demand would require holding AI systems to a differ
40、ent standard than humans.Artists can create an image in the style of another artist because copyright does not give someone exclusive rights to a style.15 For example,numerous artists sell Pixar-style cartoon portraits of individuals.16 And it is perfectly legal to commission someone to write an ori
41、ginal poem in the style of Dr.Seuss or an original song in the style of Louis Armstrong.Users of generative AI systems should retain the same freedom.CENTER FOR DATA INNOVATION 6 Figure 1:Images generated by DALL-E in response to the prompts“Elephant in the style of Van Gogh”and“The Taj Mahal in the
42、 style of Picasso,”respectively 5.Do Generative AI Systems Use Fragments of Copyrighted Content in Their Outputs?Some argue that generative AI systems are“21st-century collage tools that remix the copyrighted works of millions of artists whose work was used as training data.”17 Rather than producing
43、 unique output,these critics claim that generative AI systems are merely stitching together fragments of copyrighted content their algorithms have ingested.However,this argument reflects a poor understanding of how generative AI systems work.Generative AI systems do not produce remixes of existing c
44、ontent.They are not,as some might mistakenly imagine,taking small samples of various works,altering them,and then recombining them in a new order.Instead,generative AI systems use massive amounts of training data to create incredibly complex prediction models that allow them to produce realistic con
45、tent in response to specific prompts.For example,OpenAIs GPT-3 large language model trained on 45 terabytes of text with 175 billion parameters.18 The DALL-E 2 image model trained on 250 million images with 3.5 billion parameters.19 When prompted to“write a story about a duck on the moon”or“create a
46、 picture of a duck on the moon,”these models are not searching through existing data to find the closest match,but instead are generating new content that fits certain parameters based on the statistical patterns they have observed in the training data.For example,a“duck”consists of certain essentia
47、l elements,such as a bird with a short neck,stout body,and webbed feet.Each of these elements has its own range of acceptable parameters:colors,proportions,etc.The AI model does not CENTER FOR DATA INNOVATION 7 understand any of these parameters(and indeed,the parameters are likely much more abstrac
48、t than this example),but it is uses them to generate high-quality output.GENERATIVE AI DOES NOT EXCUSE OTHER ILLEGAL ACTS Many of the concerns about generative AI are misguided and reflect a tendency for fear to outpace understanding of emerging technologies.20 Indeed,techno panics about AI are not
49、new:Fears about AI taking jobs,destroying privacy,hiding bias,and subjugating humanity run rampant not only in dystopian science fiction novels but also among members of the press,policymakers,and professional pundits.21 While critics are wrong to argue that generative AI presents a threat to copyri
50、ght owners legal rights,there are legitimate IP issues for policymakers to consider.This section discusses some of the ways people can infringe on IP rights and the policy implications for generative AI.1.Infringing on Copyrights of AI-Generated Works Individuals who use AI to create content deserve