‘Patents for Artificial Intelligence’ – Most Laughable Issue

November28, 2017 (C) Ravinder Singh progressindia2015@gmail.com

It is TRAGIC a nation of 1.3b can’t have Intelligent IPR Policy and Program– and there is no one to talk about it and LEAD India through IPR Crisis.Pravin Anand, Attorney MISLED people – WIPO article ‘The Next Rembrandt’ as annexed never talked of PATENTS FOR ARTIFICIAL INTELLEGENCE, DIDN’T EVEN FAVOR COPYRIGHT – Creating new picture from data generated from 346 Paintings. Artificial Intelligence isCOMPLEX THOUGHT PROCESS like in Chess – Our Brains makes final decision.

From Professional Inventors view point –

 

Ø  As Top Chess Player at one time – I Didn’t Sleep Until I Find Ways to COUNTER opponents moves – Brain automatically Programmed theTHOUGHT PROCESS @ tbps Speed– I was getting OPTIONS to choose with risk indicated and based on experience make best move.Game of Chess can be recorded and protected by Copy Right – It makes no sense to ‘Protect its Artificial Intelligence’ or Thought Process.THOUGHT PROCESS itself was ‘Controlled by Mood’ – MIX of Risk and Aggression.

Ø  Patents are granted for FINAL PRODUCT as CLAIMED in application – not for background processes and can’t be changed – need New Patents for any Improvement and PATENTS CAN BE LICENSED.

Ø  Next Rembrandt can’t be Sold as ‘Painting of Rembrandt’ and IMAGES of Rembrandt can be downloaded FREE. Printed on Home Printers in hundreds.

Ø  If P&G decides to make GILLETTE Blades by 3D Printing Process –its Patent shall be valid.

Ø  Patents are Granted for ‘New Products to Promote Commercialization Of New Useful Technology.’ Not protecting INDIAN INVENTOR’s PRODUCTS led to decline of Indian Industry. Not a single Indian INVENTED Product could be Commercialized like ‘Gillette Razor’ on Global Scale so far.

Ø  Patents made R&D in everything Possible – Drug Molecule, or Gillette Blade or Engines for Jetliners or Apple Phones, LED TVs etc. Patents made HUMAN DEVELOPMENT Possible. Progress from Telegram to Telephone to Wireless >> to 5G & Optic Fiber.

Ø  Pravin Anand wanted Patents for SINGLE PICTURE produced by Computer Programs not an Expensive Painting. What makes PAINTING worth $100m is its Exclusivity. PICTURE may not be worth a penny.

Ø  Patents are GRANTED for HUMAN CREATIVITY – not picture generated by Computers.

Ø  Artificial Intelligence has not addressed Indian Problems, Floods, Pollution & Traffic of Bengaluru.

 

CII annually organizes meet WIPO on Patents and IPR for the awareness of Indian Industry but Industry representation is declining – most of the Speakers were Patent Attorneys or non-Inventors or IPR holders.

 

CII admitted in the inaugural session that INDIA HAD MISSED THE PAST INDUSTRIAL REVOULTIONS – but didn’t tell India shall miss the 4th or even 5th Industrial Revolution also if we don’t .

 

1st or 2nd and 3rd INDUSTRIAL REVOLUTIONS ARE NOT ENTIRELY DEAD and still evolving. Gadkari is talking of 1st revolution – WATER WAYSand GOI has many Stupid Programs to develop Waterways in Rivers which run dry post monsoon. Electric Railways in 2nd IR was dead in USA in motor Car era, Trams were not supported since introduction of Diesel Buses but Electric Transport is common in many Cleanest Cities of the World. Trains in India still operate at less than Steam Loco 1st IR days in Speed.

 

Ø  24×365 water supply was standard in USA for 100 years, not yet in India.

 

Ø  $100T of Development is yet to place like Homes, Power, Food Processing, Infrastructure etc.

 

Contrary to general perception Delhi had ‘SMART ENERGY METERS IN HOMES’ since 2004 – ‘Though Most SMART FEATURES Were Disabled’. Computerized meters cost 10 times more perform generally same Functions as Electro-Mechanical energy meters and most of the T&D is still 2nd IR Era.

[We are into the era of Industry 4.0 or the fourth Industrial Revolution dictated largely by information and data technology. India has the potential of becoming an important player globally unlike our absence during the earlier industrial revolutions and benefit from it by leap frogging to high technology domain. Artificial Intelligence (AI) would be the key driver manifesting itself in many different roles including Social, Mobile, Analytics and Cloud (SMAC) technologies, Internet of Everything including IOT, 3 D Printing, integrated manufacturing, Machine to Machine communication, modern biologics and so on. AI is predicted to outsmart its biological counter parts and thus poses new challenges to authorship, allocation, maintaining and enforcing IPR. AI is no longer futuristic; it is the amazing present. As AI comes closer to the human IQ of 100 and then surpasses it to reach 500 and 5000, our brains will fail to comprehend what it would really mean; we do not have the vaguest idea. AI systems are capable of inventing. Who would own the IPR including patents, copyrights and designs- becomes a food for thought across the globe.]

About The Next Rembrandt – The Next Rembrandt is a computer-generated 3-D–printed painting developed by a facial-recognition algorithm that scanned data from 346 known paintings by the Dutch painter in a process lasting 18 months. The portrait consists of 148 million pixels and is based on 168,263 fragments from Rembrandt’s works stored in a purpose-built database.

Ravinder Singh, Inventor & Consultant, INNOVATIVE TECHNOLOGIES AND PROJECTS

Y-77, Hauz Khas, ND -110016, India. Ph: 091- 8826415770, 9871056471, 9650421857

Ravinder Singh* is a WIPO awarded inventor specializing in Power, Transportation,

Smart Cities, Water, Energy Saving, Agriculture, Manufacturing, Technologies and Projects

http://www.wipo.int/wipo_magazine/en/2017/05/article_0003.html

Artificial intelligence and copyright

October 2017

By Andres Guadamuz, Senior Lecturer in Intellectual Property Law, University of Sussex, United Kingdom

The rise of the machines is here, but they do not come as conquerors, they come as creators.

 

Google has just started funding an artificial intelligence program that will write local news articles. In 2016, a group of museums and researchers in the Netherlands unveiled a portrait entitled The Next Rembrandt, a new artwork generated by a computer that had analyzed thousands of works by the 17th-century Dutch artist Rembrandt Harmenszoon van Rijn. A short novel written by a Japanese computer program in 2016 reached the second round of a national literary prize. And the Google-owned artificial intelligence company Deep Mind has created software that can generate music by listening to recordings.

Other projects have seen computers write poems, edit photographs and even compose a musical.

Computers and the creative process

Robotic artists have been involved in various types of creative works for a long time. Since the 1970s computers have been producing crude works of art, and these efforts continue today. Most of these computer-generated works of art relied heavily on the creative input of the programmer; the machine was at most an instrument or a tool very much like a brush or canvas. But today, we are in the throes of a technological revolution that may require us to rethink the interaction between computers and the creative process. That revolution is underpinned by the rapid development of machine learning software, a subset of artificial intelligence that produces autonomous systems that are capable of learning without being specifically programmed by a human.

A computer program developed for machine learning purposes has a built-in algorithm that allows it to learn from data input, and to evolve and make future decisions that may be either directed or independent. When applied to art, music and literary works, machine learning algorithms are actually learning from input provided by programmers.

They learn from these data to generate a new piece of work, making independent decisions throughout the process to determine what the new work looks like. An important feature for this type of artificial intelligence is that while programmers can set parameters, the work is actually generated by the computer program itself – referred to as a neural network – in a process akin to the thought processes of humans.

Implications for copyright law

Creating works using artificial intelligence could have very important implications for copyright law. Traditionally, the ownership of copyright in computer-generated works was not in question because the program was merely a tool that supported the creative process, very much like a pen and paper. Creative works qualify for copyright protection if they are original, with most definitions of originality requiring a human author. Most jurisdictions, including Spain and Germany, state that only works created by a human can be protected by copyright.

But with the latest types of artificial intelligence, the computer program is no longer a tool; it actually makes many of the decisions involved in the creative process without human intervention.

Commercial impact

One could argue that this distinction is not important, but the manner in which the law tackles new types of machine-driven creativity could have far-reaching commercial implications. Artificial intelligence is already being used to generate works in music, journalism and gaming. These works could in theory be deemed free of copyright because they are not created by a human author. As such, they could be freely used and reused by anyone. That would be very bad news for the companies selling the works. Imagine you invest millions in a system that generates music for video games, only to find that the music is not protected by law and can be used without payment by anyone in the world.

While it is difficult to ascertain the precise impact this would have on the creative economy, it may well have a chilling effect on investment in automated systems. If developers doubt whether creations generated through machine learning qualify for copyright protection, what is the incentive to invest in such systems? On the other hand, deploying artificial intelligence to handle time-consuming endeavors could still be justified, given the savings accrued in personnel costs, but it is too early to tell.

Legal options

There are two ways in which copyright law can deal with works where human interaction is minimal or non-existent. It can either deny copyright protection for works that have been generated by a computer or it can attribute authorship of such works to the creator of the program.

About The Next Rembrandt

 

The Next Rembrandt is a computer-generated 3-D–printed painting developed by a facial-recognition algorithm that scanned data from 346 known paintings by the Dutch painter in a process lasting 18 months. The portrait consists of 148 million pixels and is based on 168,263 fragments from Rembrandt’s works stored in a purpose-built database. The project was sponsored by the Dutch banking group ING, in collaboration with Microsoft, J.Walter Thompson marketing consultancy, and advisors from TU Delft, The Mauritshuis and the Rembrandt House Museum.

To my knowledge, conferring copyright in works generated by artificial intelligence has never been specifically prohibited. However, there are indications that the laws of many countries are not amenable to non-human copyright. In the United States, for example, the Copyright Office has declared that it will “register an original work of authorship, provided that the work was created by a human being.” This stance flows from case law (e.g. Feist Publications v Rural Telephone Service Company, Inc. 499 U.S. 340 (1991)) which specifies that copyright law only protects “the fruits of intellectual labor” that “are founded in the creative powers of the mind.” Similarly, in a recent Australian case (Acohs Pty Ltd v Ucorp Pty Ltd), a court declared that a work generated with the intervention of a computer could not be protected by copyright because it was not produced by a human.

In Europe the Court of Justice of the European Union (CJEU) has also declared on various occasions, particularly in its landmark Infopaq decision (C-5/08 Infopaq International A/S v Danske Dagbaldes Forening), that copyright only applies to original works, and that originality must reflect the “author’s own intellectual creation.” This is usually understood as meaning that an original work must reflect the author’s personality, which clearly means that a human author is necessary for a copyright work to exist.

The second option, that of giving authorship to the programmer, is evident in a few countries such as the Hong Kong (SAR), India, Ireland, New Zealand and the UK. This approach is best encapsulated in UK copyright law, section 9(3) of the Copyright, Designs and Patents Act (CDPA), which states:

“In the case of a literary, dramatic, musical or artistic work which is computer-generated, the author shall be taken to be the person by whom the arrangements necessary for the creation of the work are undertaken.”

Furthermore, section 178 of the CDPA defines a computer-generated work as one that “is generated by computer in circumstances such that there is no human author of the work”. The idea behind such a provision is to create an exception to all human authorship requirements by recognizing the work that goes into creating a program capable of generating works, even if the creative spark is undertaken by the machine.

Addressing ambiguity

This leaves open the question of who the law would consider to be the person making the arrangements for the work to be generated. Should the law recognize the contribution of the programmer or the user of that program? In the analogue world, this is like asking whether copyright should be conferred on the maker of a pen or the writer. Why, then, could the existing ambiguity prove problematic in the digital world? Take the case of Microsoft Word. Microsoft developed the Word computer program but clearly does not own every piece of work produced using that software. The copyright lies with the user, i.e. the author who used the program to create his or her work. But when it comes to artificial intelligence algorithms that are capable of generating a work, the user’s contribution to the creative process may simply be to press a button so the machine can do its thing. There are already several text-generating machine learning programs out there, and while this is an ongoing area of research, the results can be astounding. Stanford PhD student Andrej Karpathy taught a neural network how to read text and compose sentences in the same style, and it came up with Wikipedia articles and lines of dialogue that resembled the language of Shakespeare.

Some case law seems to indicate that this question could be solved on a case-by-case basis. In the English case of Nova Productions v Mazooma Games [2007] EWCA Civ 219, the Court of Appeal had to decide on the authorship of a computer game, and declared that a player’s input “is not artistic in nature and he has contributed no skill or labour of an artistic kind”. So considering user action case by case could be one possible solution to the problem.

The future

Things are likely to become yet more complex as use of artificial intelligence by artists becomes more widespread, and as the machines get better at producing creative works, further blurring the distinction between artwork that is made by a human and that made by a computer.

Monumental advances in computing and the sheer amount of available computational power may well make the distinction moot; when you give a machine the capacity to learn styles from large datasets of content, it will become ever better at mimicking humans. And given enough computing power, soon we may not be able to distinguish between human-generated and machine-generated content. We are not yet at that stage, but if and when we do get there, we will have to decide what type of protection, if any, we should give to emergent works created by intelligent algorithms with little or no human intervention. Although copyright laws have been moving away from originality standards that reward skill, labour and effort, perhaps we can establish an exception to that trend when it comes to the fruits of sophisticated artificial intelligence. The alternative seems contrary to the justifications for protecting creative works in the first place.

Granting copyright to the person who made the operation of artificial intelligence possible seems to be the most sensible approach, with the UK’s model looking the most efficient. Such an approach will ensure that companies keep investing in the technology, safe in the knowledge that they will get a return on their investment.

The next big debate will be whether computers should be given the status and rights of people, but that is a whole other story.

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