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How science can help us make AI less creepy and more trustworthy

#artificialintelligence

Stories about racist Twitter accounts and crashing self-driving cars can make us think that artificial intelligence (AI) is a work in progress. But while these headline-grabbing mistakes reveal the frontiers of AI, versions of this technology are already invisibly embedded in many systems that we use everyday. These everyday uses include everything from fraud detection systems that monitor credit card transactions to email filters that learn not to swamp your inbox with spam. You've probably already interacted with an AI system today without even knowing it and probably enjoyed the experience. One increasingly common form of AI can be found in chatbots, a type of software that lets you interact with it by having a conversation.


How science can help us make AI more trustworthy

#artificialintelligence

Stories about racist Twitter accounts and crashing self-driving cars can make us think that artificial intelligence (AI) is a work in progress. But while these headline-grabbing mistakes reveal the frontiers of AI, versions of this technology are already invisibly embedded in many systems that we use everyday. These everyday uses include everything from fraud detection systems that monitor credit card transactions to email filters that learn not to swamp your inbox with spam. You've probably already interacted with an AI system today without even knowing it and probably enjoyed the experience. One increasingly common form of AI can be found in chatbots, a type of software that lets you interact with it by having a conversation.


How science can help us make AI less creepy and more trustworthy

#artificialintelligence

Stories about racist Twitter accounts and crashing self-driving cars can make us think that artificial intelligence (AI) is a work in progress. But while these headline-grabbing mistakes reveal the frontiers of AI, versions of this technology are already invisibly embedded in many systems that we use everyday. These everyday uses include everything from fraud detection systems that monitor credit card transactions to email filters that learn not to swamp your inbox with spam. You've probably already interacted with an AI system today without even knowing it and probably enjoyed the experience. One increasingly common form of AI can be found in chatbots, a type of software that lets you interact with it by having a conversation.


10 of the Most Innovative Chatbots on the Web

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If you've ever used a customer support livechat service, you've probably experienced that vague, sneaking suspicion that the "person" you're chatting with might actually be a robot. Like the endearingly stiff robots we've seen in countless movies – tragic, pitiful machines tortured by their painfully restricted emotional range, futilely hoping to attain a greater degree of humanity – chatbots often sound almost human, but not quite. Their speech is awkward, the cadence somehow off. It's the online equivalent of the "Uncanny Valley," a mysterious region nestled somewhere between the natural and the synthetic that offers a disturbing glimpse at how humans are making machines that could eventually supplant humans, if only their designers could somehow make their robotic creations less nightmarish. Love them or hate them, chatbots are here to stay.


Putting trust in chatbots » Banking Technology

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Artificial intelligence (AI) interfaces and chatbots could be revolutionary for financial institutions – but only if they strike the right balance between human and machine interaction, argues Jeremy Pounder, futures director at Mindshare. AI is changing the banking industry as we know it. Already, banks are using AI within everyday payments, money management and digital self-service. For instance, voice recognition technology is being used by the likes of Barclays as a form of secure ID for telephone banking customers, while challenger institution Atom Bank allows its customers to log on via a facial recognition system. AI's advanced natural language processing and machine learning means it can generalise large data sets and detect and extrapolate patterns in order to create new solutions and actions.