The Risks and Rewards of AI

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In these increasingly automated times “AI” seems to be the word, or rather the letters on everyone’s lips. Not least for the members of The Risks and Rewards of AI panel that took place at AWE this Monday. Speaking to Lianna Brinded of Quartz, Tabitha Goldstaub (CognitionX), Vince Lynch (CEO IV.AI) and Russ Shaw (Tech London Advocates) tackled a controversial topic that raises as any questions as it does answers.

For many, artificial intelligence represents the opportunity to be free of the inconvenient drudgeries of everyday life – a chance to automate the tasks we like the least and free up more time to do the things we love. Others see automation as a potential threat to work (25 million jobs will be replaced by automation within the next decade), privacy and security. Love it or loathe it, AI is already a part of our everyday lives and is set to become an even bigger one.

“Close to $2 billion dollars has been invested behind AI [and] machine learning startup businesses in the broader London tech ecosystem and I think we’re seeing some really interesting companies emerge.”

Quoting figures from a recent Atomica report, Russ Shaw kicked off the debate on a positive note and listed out just some of the ways AI has already transformed London life for the better.

“Close to $2 billion dollars has been invested behind AI [and] machine learning startup businesses in the broader London tech ecosystem and I think we’re seeing some really interesting companies emerge.”

One such company he was keen to mention was DeepMind whose DeepMind Health Initiative aims to apply aspects of AI to healthcare and bridge the gap between testing patients and treating them. Intelligent tutoring systems that promote lifelong learning and travel bots deployed by TfL were two ways that Shaw envisioned AI changing the worlds of education and transport respectively.

Approaching from a similarly utopic angle, Tabitha Goldstaub says that AI could provide “an increased sense of productivity and efficiency. [Artificial intelligence] hopefully allows humans to do the things that humans are best at and machines to do the things machines are best at.”

Goldstaub went on to highlight two ways in which AI was already starting to affect all industries. In what Tabitha calls the “back offices” of businesses, departments like finance, HR and accounting are increasingly leaning on machine learning to augment their output. The core services that businesses deliver are also moving towards automation, either in the way they communicate with customers or go about more industrial fare like algorithmic trading.

“It’s a little bit of a burning platform for a lot of businesses. The opportunity is there […] if they can get their data in order, [businesses are] able to make massive, massive changes. The exciting thing that I’ve started to see is that these companies can actually use technology to reduce their costs, increase their profits and make customers happy.”

Following on from Tabitha’s points, Vince Lynch extolled the virtues of machine learning and AI’s inherent scalability. According to Lynch, when businesses find a model that works they’re then able to point it the right direction and achieve all kinds of goals. We’ve seen this with huge brands like Netflix and Spotify and their recommendation engines. Many large enterprises are following the streaming services leads and finding ways to automate the interactions they have with customers. Lynch points out that AI means marketers are able “make more sense of who they’re speaking to and speak to them in a way that’s more efficient and more one-to-one than one-to-many.”

Though roundly positive about the emergence of automisation, the panelists concede that It’s not all wine and roses on the bleeding edge of artificial intelligence. Things can get a bit creepy.

Services that automate responses to boring emails based on your previous messages. Algorithms that track positive and negative online chatter around upcoming films, adding or removing trailer scenes accordingly. Artificial intelligence platforms that trace and read the emotions on a human face as they watch videos. All things that have great implications for advertisers, but that also raise pertinent questions around privacy. Especially when things like the Cambridge Analytica scandal and Facebook data breaches are becoming more regular.

“It’s becoming part of everyday language to feel like we’re not 100% sure or happy with Facebook having all of this data on us,” admits Tabitha Goldstaub. Consumers are growing increasingly suspicious of the very same technology that’s supposed to make all our lives easier. This sentiment will only deepen as artificial intelligence becomes more embedded in our basic infrastructure.

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