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The practice of Artificial Intelligence (AI) is visible all over the world. From petrol stations that are using Big Data in price-setting in order to gain competitive advantages to evolving techniques in stem cell therapy, the opportunities of machine learning seem endlessly.

Have you already heard of Ross? Well, it’s the lawyer’s new colleague that can do anything except fetching them coffee. This piece of AI software uses IBM Watson’s supercomputing power to crunch mountains of Big Data and learns itself over time. When a lawyer asks Ross legal questions, it will give answers with relevant laws and jurisdiction. The possibly best part of Ross is that lawyers can scale their abilities and work more efficient which makes law firms able to charge lower fees. With almost 80% of Americans who can’t afford a lawyer, this big pool can be served with the implementation of Ross in law firms. (Businessinsider, 2017).

The question if lawyers can be replaced by robots was already answered in the early ‘90s by Jaap van den Herik, professor Information Technology at the University of Leiden. He stated that computers can judge certain parts of justice because it’s a specialised task and computers master specialised tasks. His ideas were recently supported by Dana Remus, professor at the North Carolina School of Law, and MIT-economist Frank Levy who published an article about the replacement of lawyers. They concluded that robots are able to ‘sort’ and ‘reason’ far more efficient than humans can (Mols, 2017).

The main obstacle of using current technology as full-fledged lawyers, is that it’s very complex to automate two aspects of lawyers’ work (context and emotion). Lawyers must take all possible circumstances into account when making judgements. With the missing of those abilities in AI software, it’s not yet possible to replace lawyers by robots.

But what about the future? With Facebook shutting down their robots after they invent their own language, nothing seems impossible for machine learning (Griffin, 2017). Not even being a judge.

Bao Pham

415129

 

References

Griffin, A. 2017. Facebook’s AI robots shut down after they start talking to each other in their own language. Retrieved from: http://www.independent.co.uk/life-style/gadgets-and-tech/news/facebook-artificial-intelligence-ai-chatbot-new-language-research-openai-google-a7869706.html

Mols, B. 2017. Kunnen robots rechtspreken? Retrieved from: https://dekennisvannu.nl/site/artikel/Kunnen-robots-rechtspreken/8182

Weller, C. 2017. The world’s first artificially intelligent lawyer was just hired at a law firm. Retrieved from: http://www.businessinsider.com/the-worlds-first-artificially-intelligent-lawyer-gets-hired-2016-5?international=true&r=US&IR=T

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Keeping in mind that you don’t outsmart the competition by doing the same, a Shell-branded petrol station in the Netherlands takes competitive advantage of advanced dynamic pricing. In corporation with a Danish data analytics company (a2i Systems) the petrol station sets their prices based on dynamic retail fuel pricing (The Register, 2017).

Open competition between companies selling similar products commonly leads to price wars. The retail fuel industry is a good example of a competition where companies are pushing each other in a bloodbath by dropping petrol prices.

Where older pricing software are originally based on simple rules such as always keeping prices lower than the competition, advances in Artificial Intelligence (AI) allow retail and wholesale firms to move beyond dynamic prices for fast-moving goods. Data analytics company a2i Systems developed pricing software that’s focussed on consumer behaviour by applying AI to Big Data. The system uses mountains of historical and real-time data to identify the optimal price setting throughout the day. By learning when raising prices drove customers away and when it didn’t, the software is able to live up to the price sensitivity of customers (a2i Systems, 2017).

Chief Executive of a2i Systems Ulrik Blichfeldt said that this software is developed to benefit both the customer as well as petrol stations. “This is not a matter of stealing more money from your customer. It’s about making margin on people who don’t care, and giving away margin to people who do care,” he said (The Australian, 2017).

On the other hand, anti-trust laws could be challenged by the rise of AI pricing. Former anti-trust lawyer and now law professor Maurice Stucke said that eventually consumers will be going to end up paying a higher price (The Australian, 2017).

Makers and users of AI pricing state that whatever tools are used, the business logic remains human. What do you think? Will AI pricing help firms in fast-moving goods industries to stay out of the bloodbath or will it make collusion easier and aliens to fair competition?

Bao Pham

415129

References:

A2iSystems, 2017. Pricecast Fuel: retail fuel pricing – management and optimization. Retrieved from http://a2isystems.com/files/pdf/PriceCast%20Fuel%20Product%20Folder%20(’15).compressed.pdf

Orlowski, A. 2017. AI-powered dynamic pricing turns its gaze to the fuel pumps. Retrieved from https://www.theregister.co.uk/2017/05/24/aipowered_dynamic_pricing_petrol/

Schechner, S. 2017. Consumers lose, margins win when robots set the prices. Retrieved from http://www.theaustralian.com.au/business/wall-street-journal/consumers-lose-margins-win-when-robots-set-the-prices/news-story/f6729db857e74963921dfa3d00953ed7