On copyright infringement and AI (GS Paper 3, Science and Technology)
Why in news?
- The recent decision of the U.S. Supreme Court in the Andy Warhol Foundation for the Visual Arts Inc. versus Goldsmith et al. has added more unpredictability to the process of being exempted from copyright infringement liabilities.
- The judgment is set to have implications for how to regulate a powerful form of artificial intelligence.
To what extent does copyright law protect artists?
- Copyright law protects the work of diverse artists, including photographers, and provides a set of exclusive rights for artists over their creative output. This includes controlling the manner in which others reproduce or modify their work.
- However, these exclusive rights are balanced with the rights of the users of such work, including other artists who might want to build on or comment on them, with the help of diverse exceptions under the copyright law.
What is exempt from infringement liability?
- Different jurisdictions follow different approaches to exceptions. Some countries, particularly those in continental Europe, adopt the ‘enumerated exceptions approach’, the use in question needs to be specifically covered under the statute to be considered as an exception to copyright infringement.
- Some others, including the U.S., follow an open-ended approach that does not specify exemptions beforehand, instead, they have guidelines about the types of uses that can be exempted.
- The U.S. courts primarily consider four factors when determining whether a particular use can be considered to be an instance of fair use:
- the purpose and character of the use;
- the nature of the copyrighted work;
- the amount and substantiality of the portion taken by the defendant, and
- the effect of the use on the potential market of the plaintiff’s work.
- Of these, the U.S. courts have been giving the highest importance to the first factor — whether the use of something can be considered “transformative” has often played the most critical role in determining the final outcome in a fair-use case.
What is the AWF case?
- Known for her concert and portrait shots, Lynn Goldsmith photographed the famous musician Prince in 1981. One of those photos was licensed in 1984 to Vanity Fair magazine for use as an “artist reference”.
- The licence specifically said the illustration could appear once as a full-page element and once as a one-quarter page element, in the magazine’s 1984 November issue. Vanity Fair paid Ms. Goldsmith $400 for the licence.
- It then hired the celebrated visual artist Andy Warhol to work on the illustration. Mr. Warhol made a silkscreen portrait of Prince using Goldsmith’s photo. It appeared in the magazine with appropriate credits to Ms. Goldsmith. But while the licence had authorised only one illustration, Mr. Warhol additionally created 13 screen prints and two pencil sketches.
- In 2016, Condé Nast, the media conglomerate that publishes Vanity Fair, approached the Andy Warhol Foundation (AWF) to reuse the 1984 illustration as part of a story on Prince. But when they realised that there were more portraits available, they opted to publish one of them instead (an orange silkscreen portrait). As part of the licence to use it, they paid $10,000 to AWF, and nothing to Ms. Goldsmith.
- When the AWF realised that Ms. Goldsmith may file a copyright infringement suit, it filed a suit to declare that it had not committed infringement. Ms. Goldsmith then counter-sued AWF for copyright infringement.
What did the courts find?
- The majority of judges concluded that if an original work and secondary work have more or less similar purposes and if the secondary use is of a commercial nature, the first factor may not favour a fair-use interpretation unless there are other justifications for copying.
- In this particular instance, according to the majority decision, both Ms. Goldsmith’s photos and Mr. Warhol’s adaptations had more or less the same purpose, to portray Prince.
- The majority said that while copying may have helped convey a new meaning or message, that in itself did not suffice under the first factor. The dissenting opinion focused extensively on how art is produced, particularly the fact that no artists create anything out of a vacuum.
- Justice Elena Kagan, wrote of the need for a broader reading of ‘transformative use’ for the progress of arts and science. The dissenters also opined that Mr. Warhol’s addition of important “new expression, meaning and message” tilted the first factor in favour of a finding of fair-use.
How does this affect generative AI?
- While this dispute arose in the context of the use of a photograph as an artistic reference, the implications of the court’s finding are bound to ripple across the visual arts at large.
- The majority position could challenge the manner in which many generative artificial intelligence (AI) tools, such as ChatGPT4, MidJourney, and Stable Diffusion, have been conceived. These models’ makers ‘train’ them on text, photos, and videos strewn around the internet, copyrighted or not.
- The majority’s reliance on the commercial nature of the use may also result in substantial deviation from the established view, that the commercial nature of the use in itself cannot negate a finding of fair use. But the true extent of the implications of the verdict will be clear only when trial courts begin applying the ratio in this judgment to future cases.
What about the implications on Indian copyright law?
- There may not be any direct implications for Indian copyright law, as the framework of exceptions here is different.
- India follows a hybrid model of exception in which fair dealing with copyrighted work is exempted for some specific purposes under Section 52(1)(a) of the Copyright Act 1957. India also has a long list of enumerated exceptions.
- This said, the observations by the U.S. Supreme Court’s decision could have a persuasive effect, particularly when determining ‘fairness’ as part of a fair-dealing litigation. Then again, only time will tell which one will have a more persuasive effect, the majority or the minority.
India set to triple speed of its fastest supercomputers
(GS Paper 3, Science and Technology)
Why in news?
- India is set to dramatically scale up its supercomputing prowess and install an 18-petaflop system over the course of 2023, Earth Sciences Minister said.
Current status:
- Currently India’s most powerful, civilian supercomputers; Pratyush and Mihir with a combined capacity of 6.8 petaflops are housed at the Indian Institute of Tropical Meteorology, Pune, and the National Centre for Medium Range Weather Forecasting (NCMRWF), Noida, respectively.
- They were made operational in 2018 at an investment of ₹438 crore. Both these organisations are affiliated to the Ministry of Earth Sciences (MoES).
What are FLOPs in computing?
- FLOPs, or Floating-Point Operations per Second, is a commonly used metric to measure the computational performance especially in the field of high-performance computing (HPC) and artificial intelligence (AI).
- Floating-point operations are a certain kind of mathematical calculation using real numbers with fractional parts.
How many FLOPs can a computer achieve?
- Modern computing systems, such as CPUs (Central Processing Units) and GPUs (Graphics Processing Units), are designed to perform multiple operations simultaneously, using parallel processing techniques.
- The parallelism significantly increases the number of FLOPs a system can achieve within a given time frame. Over the years, hardware has become more efficient, exponentially increasing computing power.
- For instance, in 1961, the IBM 7030 Stretch, costing a whopping $ 7.8 million at the time, performed one floating-point multiplication every 2.4 microseconds, roughly performing 417,000 FLOPs. A PlayStation 5 today is listed to have a peak performance of 10.28 TFLOP, i.e. 10.28 trillion FLOPs.
What is a petaFLOP?
- Due to the immense computing power of today’s computers, the FLOPs metric is most often represented in terms of billions (giga), trillions (tera), or even quadrillions (peta) of operations per second (GFLOPs, TFLOPs, PFLOPs, respectively). A petaflop is thus equal to a thousand TFLOPs or 1015 FLOPs.
- Currently, the world’s fastest computer in terms of PFLOPs is the Hewlett Packard Enterprise Frontier, or OLCF-5 with the capability to touch a peak performance of 1,685.65.
Is India already using petaFLOPs computers for weather forecasting?
- The NCMRWF houses ‘Mihir’, a 2.8 petaflop supercomputer, while the Indian Institute of Tropical Meteorology (IITM), Pune, is home to ‘Pratyush’, a 4.0 petaflop supercomputer.
- These were launched in 2018 and will be decommissioned once the new supercomputer is unveiled.
- NCMRWF will be allocated eight PFLOPs computing power with the remaining 10 PFLOPs going to IITM. The Pune-based institute requires higher power as it deals with seasonal weather forecasts while the NCMRWF deals with medium-range forecasts for a period extending three to seven days in advance.
