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Artificial Intelligence

Legal Consulting Firm Believes Artificial Intelligence Could Replace Lawyers by 2030

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According to Jomati Consultants LLP, artificial intelligence and robotics will change the entire legal landscape in just over a decade.

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Tony Williams, the founder of the British-based legal consulting firm, said that law firms will see nearly all their process work handled by artificial intelligence robots. The robotic undertaking will revolutionize the industry, “completely upending the traditional associate leverage model.”

In this report, ‘Civilisation 2030: The Near Future for Law Firms’ we explore what will be the impact on clients and law firms of three key factors that shape the global economy: demographics, the growth of global cities and megacities, as well as the introduction of artificial intelligence (AI) and robotics into both the industrial and professional sectors. The report closely analysed macro-economic data and key trends then considered how these will develop to 2030.

The report predicts that the artificial intelligence technology will replace all the work involving processing information, along with a wide variety of overturned policies.

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AI bots could foreseeably take over any work with a systemic component that involves the processing of information. That includes low-level knowledge economy work, like due diligence, that is currently performed by very junior lawyers.

Williams also said that these knowledge bots would go beyond the retrieval function of today’s “knowledge management” software and work on the material, impacting associate and paralegals majorly.

While the report leans heavily toward the artificial intelligence technology, not everyone believes every facet of the legal structure can be automated. Ken Chasse, a lawyer at Barrister & Solicitor for more than 48 years, wrote an independent report in October 2014 that says legal advice cannot be automated, by nature.

Also read: The Young Fear the Coming Machine Overlords

Keeping the Human Touch in Artificial Intelligence

AIIn Canada, the legal landscape is faced with proposals for alternative business structures (ABS’s) that allow the ownership of law firms by investors, otherwise non-lawyer people or entities. These ABS’s want legal services to provide non-legal services as well as automate legal services by software applications.

Chasse thinks that services can be automated by the current legal structure itself, without the need to ABS’s or investors.

“All of the new software developments are based upon improving the handcraftsman’s method of law firms delivering routine legal services. But they cannot automate legal advice services.”

The main issue with the current legal structure is that it’s viewed as overpriced and costly, according to the report. But Chasse thinks the current tools at hand are far more cost-efficient with the aid of support services. He claims in his own report that law societies can process, and have processed, more than 5,000 legal opinion services per year by working with support services.

The previous report on artificial intelligence replacing many facets of the legal structure by 2030 mentions the human element as well. Williams says that from a client’s perspective, artificial intelligence will be nothing more than a production tool. The robots proposed could not make decisions based on human factors.

“Clients would greatly value the human input of the firm’s top partners, especially those that could empathize with the client’s needs and show real understanding and human insight into their problems.”

The main purpose of the bots is to save money, according to Williams, as they would simply process minor work, 24 hours a day; never needing to rest or ask for a raise while eliminating jobs that cost $100,000 or more in salary. The work would make legal services more affordable, and partners that were once paid quite well might find themselves with a lowered salary or out of a job, Williams said.

Whether or not artificial intelligence will take out the legal structure is still unknown, as the report was only speculation. The consulting firm did not develop any artificial intelligence technology, or at least did not disclose such information in the report, so it is still unclear whether or not their findings are accurate.

Images from Wikimedia Commons and Shutterstock.

Important: Never invest (trade with) money you can't afford to comfortably lose. Always do your own research and due diligence before placing a trade. Read our Terms & Conditions here. Trade recommendations and analysis are written by our analysts which might have different opinions. Read my 6 Golden Steps to Financial Freedom here. Best regards, Jonas Borchgrevink.

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Clay Gillespie a writer and reporter for many different platforms across the tech industry. He holds a B.S. in Public Relations from Ball State University, and freelances for different clients in technology and cryptocurrency. For more information, visit his personal website, claygillespie.com.




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14 Comments

14 Comments

  1. John M. Kuchta

    January 2, 2015 at 3:53 pm

    And to think, at least half a dozen of my friends just spent upwards of 100K on law school

    • Zack Ballenger

      January 2, 2015 at 10:17 pm

      Maybe they learned how to get out of paying the loans.

      • JWHacket

        January 3, 2015 at 1:43 am

        Nah, they learned how to fall down in a store and sue the owner.

  2. Orion73

    January 2, 2015 at 4:21 pm

    I can see legal research being performed by bots, but when it gets to trial your outcome depends largely on two things: (1) personal relationship with the judge and opposing counsel, and (2) persuading the jury.

    • godforall

      January 2, 2015 at 4:48 pm

      “persuading the jury” in the US maybe

  3. randcraw

    January 2, 2015 at 4:47 pm

    Makes you wonder, could they automate the jury too?

    • Scott Bisset

      January 2, 2015 at 5:05 pm

      Probably, they could automate it all. After all we’re only Biological Machine made by nature there’s no law in the universe saying we can’t make equivalent if not better version of ourselves. Like A.I. computational entities.

      • Citizen 01001011

        January 2, 2015 at 9:50 pm

        On a purely scientific basis, this is far too reductionistic: just because we have a material existence and there are mechanistic aspects to us does not make us mere machines. Our brains have quantum properties that make us far different from any machine.

        Yes, rote parts of legal work can be automated by expert systems — but you cannot replace a lawyer’s intellectual insight, psychological perception, or social skills with an expert system. To think you can demonstrates a lack of understanding of the legal profession (among others) and an unjustified confidence in what A.I. can do. (And I think the term “expert system” is better than “artificial intelligence”; less misleading, if not as sexy…)

        Would you want your contract dispute handled by a fifth-generation Siri app?

  4. John Koleszar

    January 2, 2015 at 11:43 pm

    It’ll be interesting when it replaces judges too….

  5. Kite23

    January 3, 2015 at 3:03 am

    How long til engineer duties are automated? That would be the REAL price cutter.

  6. Andrew

    January 3, 2015 at 3:25 am

    Welcome to the NWO, yeah I’m gonna go and kill myself now brb.

  7. Gilbert Sylvain

    January 4, 2015 at 12:09 pm

    I agree. I will trust A I before a top lawyer. A high class lawyer with empathy? What a joke. Lol lol.

  8. Karianne Knezevic @ Happonomy.

    June 15, 2015 at 11:47 am

    It is very likely that in the near future lawyers will benefit from artificial intelligence to speed up certain procedures, reduce workload and save costs, but when it comes to taking over a lawyers main job; to deliver justice, can we really trust this important role in society to a machine?
    http://www.happonomy.org/our-world/feel-at-ease/lawyers-and-judges

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Artificial Intelligence

YEXT: An Invisible Force In Artificial Intelligence

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YEXT, Inc. (NYSE: YEXT) is one of those behind the scenes companies involved in Intelligence Search that plays an important role in Artificial Intelligence. What does that mean? Remember the Amazon commercial? “Eco, order a 12” Pizza with pepperoni from Stromboli’s and have it delivered”.

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Today the vast majority of online searches go through third-party sources such as data aggregators, governmental agencies and consumers. The net result of this third party sourcing has been to produce “best guess” data that can often miss or misstate the target data field.

YEXT developed a better way to source critical digital knowledge.  For example business clients use YEXT to update public facts about their brands. They are building their based on the rapid and ever changing nature of data.  So far the YEXT Knowledge Network offers over 100 services to more than 110 corporate clients and has over $150 million in annual revenue.  So could YEXT play a key role in AI,  the next big thing?

How YEXT Works

Most of us are familiar with big time search engines like Google, Google Maps, Facebook, Instagram, Bing, Cortana, Apple Maps, Siri and Yelp.  These pioneering companies are the major drivers in information search today.  However, we also know, their accuracy is not exactly ideal.  

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This is where YEXT steps in.  Their knowledge engine platform lets business manage their digital knowledge in the cloud and sync it to over 100 services including the kingpins of search noted above.

Intelligent Search is the structured information that a business wants to make publicly accessible. In food service it could be the address, phone number or menu details of a restaurant; in healthcare, the health insurances accepted by a physician or the precise drop-off point of the emergency room at a hospital campus; or in finance, the ATM locations, retail bank holiday hours or insurance agent biographies.

Artificial Intelligence Offers a Potential $10 Billion Market

Improving search results in general is nice but not very sexy.  It doesn’t make you want to beg for more information.  However, when you consider the role of Artificial Intelligence (AI) in our evermore data intense world, the importance of Intelligent Search and the opportunities for YEXT becomes a compelling story.  

The AI trend is already underway as YEXT is increasingly using the structured data on their platform to expand or add new integrations with vertically specialized applications, voice-based search and AI engines.

Just Right For Big Data Applications

YEXT customers use their platform to manage their digital knowledge covering over 17 million attributes and nearly one million locations. These customers include leading businesses in a diverse set of industries, such as healthcare and pharmaceuticals, retail, financial services, manufacturing and technology.

Major customers include: AutoZone, Ben & Jerry’s, Best Buy, Citibank, Denny’s, Farmers Insurance Group, H&R Block, HCA, Infiniti, Marriott, Michael’s, McDonald’s, Rite Aid, Steward Health Care and others. The list is growing.

Management believes the market for digital knowledge management is large and mostly untapped with over 100 million potential business locations and points of interest in the world equaling over $10 billion.  

Shooting For Acquisitions and Broad AI Penetration

Founded in 2006 by serial entrepreneurs Howard Lerman (CEO) and Brian Distelburger, President these two are typical software guys whose vision appears much more broad based the their current focus with YEXT.  Here is where the prospectus from their April 2017 IPO offers some mystery and excitement to the story.

Unlike most rapid growth tech companies YEXT had no urgent need to go public.  They generated almost $60 million in gross profit in 2016 before heavy marketing costs resulted in a loss of $26.5 million.  Even so, they still ended the year with $20 million in cash. That’s a fair distance from being destitute.

The company’s real need for the IPO was to establish a liquid public market for the stock. They raised about $123.5 million, all of which will go into the bank.  The company is debt free and there are no insiders selling stock.  Very interesting.

Strong  Financial Results

For the latest reported nine months ended October 31, 2017 revenues grew 38% reaching $122 million.  The good news is the gross profits reached a record 75% or $90 million.  All of this was spent on sales and marketing to expand the business.  When all the beans were counted, YEXT lost $50 million producing a $30 million negative cash flow.  The balance sheet remains liquid with $120+ million in cash and securities.

FYI: In spite of some top notch bankers underwriting its IPO and analysts from those same five firms covering the company, the stock has done almost nothing for investors.  This $1.1 billion market cap was recently hanging out around $12 about the same as the IPO price.

Featured image courtesy of Shutterstock.

Important: Never invest (trade with) money you can't afford to comfortably lose. Always do your own research and due diligence before placing a trade. Read our Terms & Conditions here. Trade recommendations and analysis are written by our analysts which might have different opinions. Read my 6 Golden Steps to Financial Freedom here. Best regards, Jonas Borchgrevink.

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4.4 stars on average, based on 76 rated postsJames Waggoner is a veteran Wall Street analyst and hedge fund manager who has spent the past few years researching the fintech possibilities of cryptocurrencies. He has a special passion for writing about the future of crypto.




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Artificial Intelligence

The End of Human Money Managers

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robot

Quantitative Easing by central banks around the world has led to dramatic changes in the money management industry over the past six years. Not only have we seen increasing regional differences, but stock picking has also become more difficult as the money injected into the markets by central banks has lifted pretty much everything, regardless of valuation and the future potential of the asset.

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Investors have become impatient and highly demanding as a result of years of low interest rates. Old mutual funds are being swapped out for new, better ones at a record pace as investors hunt for higher ROI. Passive income has become a trend, and ETF’s and automated investment strategies are getting more and more popular as a result.

How do money managers attract capital?

There are three main factors that determine how much capital a money manager is able to attract from investors:

  1. Track record
  2. Strategy
  3. Technology

Changes in any of these factors can have a big impact on investors’ willingness to let the fund manager keep the money they have already invested with him, or receive new money.

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Technology has been a very important driver over the past few years. Data-driven, or quantitative funds are gaining an ever-increasing market share in the money management space. This is happening because more and more people are realizing the obvious benefits that this type of money management has to offer.

Investors increasingly prefer the robustness, speed, and predictability that automated money management can provide. When it comes to robustness, we are referring to both the physical and psychological aspect of it.

Humans vs. robots

Humans are pretty much the opposite of “robust,” in the true sense of the word. Our emotional state on any given day can make us react to things in different ways than we otherwise would have done, potentially leading to critical mistakes for a trader.

As humans, we may miss trading opportunities in the market because we came in late, took a day off, or simply didn’t pay attention at any given moment.

Robots are obviously not affected by fatigue and lack of focus. For example, a robot can monitor the stock or cryptocurrency market and trade just like a human trader would do, with the only difference being that the former (arguably) does it better and never needs to rest.

Thanks to the high computing power available today, robots can collect, verify, analyze, and react to opportunities long before a human will even understand that such opportunities exist.

Data-driven approach to fund management is taking over

A recent ranking by Institutional Investor Magazine revealed that out of the world’s 100 biggest hedge funds, five of the top six spots were held by data-driven funds.

On first place was Ray Dalio’s Bridgewater Associates with $122.3 billion under management. In 2016, Bridgewater grew the amount of money under management by 17%.

Renaissance Technologies, the company known for having hundreds of mathematicians, physicists, and coders on their payroll, came in fourth with $43 billion.

Two Sigma, which is also well-known for using technologies like AI and machine learning, came in fifth with $39 billion under management. Their increase from the year before was 28%.

According to Barclays, $500 billion are now invested in purely data-driven funds, while JP Morgan claims that data-driven trading strategies accounts for a whopping 90% of global trading volumes in stocks.

The core objective of any money manager is always to follow the money. That’s why we are seeing a race right now by the big players in the industry to use words like “technology-driven,” “artificial intelligence,” and so on. Whether or not that is true is not always a concern for them.

Money managers are destined to unemployment

Those who are really in trouble because of this huge change are the money managers themselves. Most of them will likely lose their jobs over the next few years. There is simply very little need for their very expensive services anymore, as robots are able to do the same thing in a much cheaper and more consistent way.

As legendary investors Jim Rogers predicted a few years ago, the stock brokers will become broke and the farmers are going to be driving Lamborghinis. Maybe there will finally be some truth to this.

Featured image from Pixabay.

Important: Never invest (trade with) money you can't afford to comfortably lose. Always do your own research and due diligence before placing a trade. Read our Terms & Conditions here. Trade recommendations and analysis are written by our analysts which might have different opinions. Read my 6 Golden Steps to Financial Freedom here. Best regards, Jonas Borchgrevink.

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4.3 stars on average, based on 32 rated postsFredrik Vold is an entrepreneur, financial writer, and technical analysis enthusiast. He has been working and traveling in Asia for several years, and is currently based out of Beijing, China. He closely follows stocks, forex and cryptocurrencies, and is always looking for the next great alternative investment opportunity.




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Artificial Intelligence

Bitcoin Giant Bitmain Enters the High Stakes AI Race

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Artificial Intelligence

The Sophon, named for a fictional proton-sized supercomputer, could be the tool to train neural networks in data centers worldwide. It is the latest project being developed by Bitmain Technologies Ltd., the bitcoin mining giant that has carved out a dominant position in bitcoin mining.

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Such chips, called application-specific integrated circuits (ASICs), could unleash a new wave of distributed computing, according to Michael Bedford Taylor, a University of Washington professor who studies bitcoin mining and chips.

Sophon is due to debut before the end of the year.

Bitmain Has The Know-How

Bitmain has the background to play a role in the expanding artificial intelligence industry. The company designs the silicon that goes in bitcoin mining equipment, assembles the machines and sells them worldwide, in addition to its own bitcoin mining operation and the ones that it manages for other mining pools.

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Bitmain’s founders are not averse to playing a spoiler role.

Jihan Wu, the co-founder of Bitmain, supports the New York Agreement that seeks to double the bitcoin block size under the SegWit2X proposal, a move that some in the bitcoin community view as an attempt to give the miners control over bitcoin.

Some also believe Wu was behind the recent bitcoin split known as bitcoin cash, which at least one of Bitmain’s miners supported, a contention that Wu has denied. Wu points out that he was among the supporters of Bitcoin Unlimited, an earlier bitcoin scaling proposal that did not get activated.

Why Wu Supports Forks

Wu nonetheless said splits should be allowed. He said a fork is inevitable since people in the bitcoin community do not agree on how to best scale bitcoin.

Wu met Micree Zhan, Bitcoin’s co-founder, when Zhan was running DivaIP in 2010, a company that made a device that allowed a user to stream a TV show on a computer screen.

In 2011, Wu needed a chip designer to build a mining operation and approached Zhan. Zhan first designed an ASIC to run SHA-256, the cryptographic calculation used in bitcoin, at maximum efficiency. It took him six months to finish the job. His first rig, Antminer S1, was ready in November 2013.

Bitmain felt the sting of the 2014 Mt. Gox meltdown. But by 2015, bitcoin’s price bottomed out and later recovered. In the meantime, Bitmain introduced its Antminer S5.

Bitmain now employs 600 people in Beijing.

Also read: Bitmain clarifies its ‘bitcoin cash’ fork position

Ready To Take On Google

Bitmain has since developed a deep learning chip with improved efficiency. Users will be able to build their own models on the ASICs, enabling neural networks to deliver results at a faster pace. Google’s DeepMind unit used this technique to train its AlphaGo artificial intelligence.

Bitmain plans to sell the chips to any company looking to train its own neural nets, including firms like Alibaba, Tencent and Baidu. Bitmain could build its own data centers with thousands of deep learning rigs, renting out the computation power to clients the way it does with bitcoin mines.

Professor Taylor said companies like Bitmain that have excelled in bitcoin mining could take on the Googles and Nvidias since they have developed the skills to survive in an ultra-competitive and highly commoditized industry, and have the system level design expertise and the ability to reduce data center costs.

Important: Never invest (trade with) money you can't afford to comfortably lose. Always do your own research and due diligence before placing a trade. Read our Terms & Conditions here. Trade recommendations and analysis are written by our analysts which might have different opinions. Read my 6 Golden Steps to Financial Freedom here. Best regards, Jonas Borchgrevink.

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3.9 stars on average, based on 8 rated postsLester Coleman is a veteran business journalist based in the United States. He has covered the payments industry for several years and is available for writing assignments.




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