• August 24, 2020

AI taking over: will machine learning replace humans?

AI taking over: will machine learning replace humans?

AI taking over: will machine learning replace humans? 1024 576 DataLit

Author: Marco Belmondo (Chief Marketing Officer at Datrix group)

Is it possible for machine learning to replace humans?

In his 2018 “The future of jobs” report the World Economic Forum analysts forecasted a future in which workforce transformations are deeply affected by AI taking over. According to the report in only four years time (2018-2022) we are going to witness a deep change in the way we work, with automation and AI based technologies causing many human jobs being no more necessary (because they can be efficiently and substituted by an AI driven machines)  but at the same time generating increasing demand for new technology connected roles and making it essential hiring a highly skilled workforce.

AI taking over: what changes in the workforce ecosystem

In particular it is expected that by 2022 42% of total task hours and 57% of specific work tasks (as opposed to 29% and almost none in 2018) will be performed by machines, with even tasks such as communicating, interacting, coordinating, decision making beginning to be automated. However, new jobs are going to emerge as the result of this process, leading to the displacement of 75 million jobs on one hand, but on the other hand to the emergence of 133 million new roles, that are more adapted to the new division of labour between humans and algorithms.

AI vs human learning: is AI substituting humans?

So to go back to our main question: will AI taking over cause human learning and jobs to be replaced by the machines? The answer is at once affirmative and negative.  

AI is going forward at a faster and faster pace, and is beginning to be applied in fields that beforehand were exclusively human, like advising, reasoning, decision making, even writing: in 2020 for example Microsoft substituted dozens of its journalists and content editors with AI driven algorithms and many companies have some of their reports written by AIs (for example Forbes has Quill™an AI which analyzes data and generates perfectly written narratives or reports) . But of course sci-fi scenarios in which super intelligent computers completely dominate the human race are at the moment only speculative fiction. AI is not even remotely close to matching true human reasoning and learning (just think of automatic chatbots…is the experience even slightly safisfactory?).

Real world AI: where algorithms shine

On the contrary on specific tasks involved with automating or optimising things (for example examining enormous loads of data and taking conclusions from that) AI can achieve results that humans cannot even dream of. So AI is used in medical research, a field where with its ability to examine at a light speed thousands possible design decision can really speed up new drug development; big e-commerce companies like Amazon use AI to optimize their warehouses and also to calculate how many drivers they are going to need at a given moment to fulfill the orders; financial companies use AI to scan through thousands of online transactions to identify possible frauds.

AI and humans: a reciprocal advantageous cooperation

But does this mean that AI taking over will end in machine learning replacing humans? On the contrary it seems that currently the most advanced research areas point to developing systems that help humans in doing their job better and with less effort, freeing them for more creative, human-needing issues. Of course some jobs will be lost, but more will be created and even more will become less burdensome and labour intensive.

An excellent example of this interaction human-machine is customer care: could you imagine how much a customer care agent could benefit from an AI that in real time recognizes what the customer is saying and proposes to the agent some possible solutions from which she can choose, improving greatly also the customers’ experience? Also, customer care AIs help agents improve their surveys and response rates, or understand the best time to engage community members…in this way humans are free to focus on more relevant and sophisticated aspects of their work, aspects that have to do with understanding, empathy, dialog and that only humans can truly deal with.

Another example is the ability of AI algorithms to analyze customers’ data on retailers and publishers websites with a level of granularity that highly skilled humans can achieve with only tremendous effort. The results of this analysis can then be used by human decision makers (advertisers, publishers or retailers) to better plan their campaigns or to monetize their websites in ways they had not thought possible before.

This is what Datalit.AI does: thanks to AI technology, DataLit.AI can predict users behavior profiling websites visitors with a precision unreachable without using AI tools; it can offer the most desirable ad space (the header) to multiple demand partners and then maximize the revenue by let them bid on it; it can help retailers sell their ad space by capitalizing on their non-buyer users (identified through the algorithm). Here it’s clear that AI is not overcoming humans but on the contrary is helping them in doing a better job in a shorter time. Of course the ability to use the results of AI elaborations remains at the moment an exclusive human ability, even though we cannot set certain boundaries to what the future may hold. 

Human role in human/machine interaction has changed: machines are no longer used only as a tool, they can solve problems. Humans have to define problems that the machines have to solve and to move on using the and building on the solutions they propose. So it’s perfectly clear that even a technology such as the one that DataLit.AI makes available is of no use if there isn’t someone who clearly defines a business problem or opportunity. AI without human intelligence is (still) nothing.