Why ? you ask, consider the following elements of a taxi business today:
* Cars and drivers.
Drivers may own a taxi, or they may not, depending on the market. For example, in UAE the fleet is owned by the government, in Indian it could be the driver or a private firm, US mostly individual owners.
* Matching algorithm.
Most of the modern taxi businesses like Uber, Ola, Careem, Lyft, grab etc. are based on a platform model, with the value unit being the convienience of getting a taxi whenever you want for the consumer and business on demand for taxi fleet companies, individual taxi owners, or drivers.
* Data.
The amount of data being captured about the person driving and using the taxi along with the place that these taxis are being driven is enormous.
Big enough that the modern taxi companies are slowly morphing into more of a technology company or a bank in some case. Monetizing this data is a major source of revenue directly or indirectly. Payments, lending, insurance and all sorts of financial services are part of the play now.
Out of these elements, managing the logistics around cars and drivers along with matching them to consumers is probably the most complex process, highly unpredictable and cash intensive to scale.
Needless to say, these companies are a furnace for consuming money with almost no hope of profitability. To feed the endless ambitions to scale, an “exit” or probably raising more money are the only possible directions.
An electric driverless fleet will probably simplify this major complexity, and depending on how much more data these driver less cars can capture with their complex camera system, both Audio and visual, they could prove to be a gold mine for data driven services.
Any potential risks you ask ? Watch a science fiction movie about an #artificialintelligence and let your imagination run wild.
Problems are bound to occur, anything that is a problem today was most likely conceived as a solution for something. I believe this is one of the most useful and practical applications of #ai.