Can you imagine a world without the kind of voice assistant technology provided by Amazon Alexa, Google Assistant, Siri on the iPhone or Cortana for Windows? Probably not, as we tend to take such technological leaps forward pretty much for granted. But behind the scenes there's a whole new world of machine-learning that drives their collective ability to seemingly answer any question put to them. It's not so much knowing the answer that's the technological miracle – because, well, the internet – but rather that these virtual assistants are able to understand the question in the first place. Machine-learning is, in the broadest possible terms, what you might expect in that computer algorithms can be trained to understand how to correctly respond to an input by way of a human telling it what that response should be.
Any examination of bias in AI needs to recognize the fact that these biases mainly stem from humans' inherent biases. The models and systems we create and train are a reflection of ourselves. So it's no surprise to find that AI is learning gender bias from humans. For instance, natural language processing (NLP), a critical ingredient of common AI systems like Amazon's Alexa and Apple's Siri, among others, has been found to show gender biases – and this is not a standalone incident. There have been several high profile cases of gender bias, including computer vision systems for gender recognition that reported higher error rates for recognizing women, specifically those with darker skin tones.
Finn AI, the world's leading AI-powered conversational banking technology provider, today announced that one of the world's largest financial services corporations has chosen Finn AI to help improve customer service and to enhance customer acquisition workflows. Under the terms of the engagement, Finn AI has developed a virtual assistant to pre-qualify prospects for the company's personal and small business banking products, ensuring human sales agents are engaged only when an inquiry is sales-based, thus reducing the cost to acquire. The virtual assistant also interacts with customers outside of regular call center hours, allowing the financial institution to extend their support hours to a 24/7 model. Additionally, the virtual assistant is used to expedite the product application process for new and existing customers, providing information about banking products and in-the-moment guidance, through to applying for a product. "This customer engagement is an excellent example of how Finn AI can help financial institutions achieve very specific, and often complex, business objectives," said Jake Tyler, CEO at Finn AI. "This particular use case leverages a number of our pre-built Customer Acquisition features including Smart Routing, Product Comparison, and Product Recommender. Used in combination, the customer is able to reduce distractions to sales agents while improving the consumer experience."
How often, or little, they're used by employees to increase their efficiency and improve customer satisfaction. For IBM, the only way to make AI a core part of the workflow across entire companies is to take a cue from a decades-old office staple: email. It's dangerous to think of AI as a magic tool, said Daniel Hernandez, VP of data and AI at IBM, speaking at the Gartner IT Symposium/Xpo in Orlando, Florida last week. Instead, it should be seen as a strategy to empower staffers, helping them make more effective decisions through data while boosting employee experience. "Email gets no respect because it's boring," said Hernandez.
This research summary is just one of many that are distributed weekly on the AI scholar newsletter. To start receiving the weekly newsletter, sign up here. Conversational assistants are one of the most interesting AI advances that we have witnessed recently. So far, we have seen them increasingly become a meaningful part of our personal lives as well as businesses to improve customer service. No doubt the future of these assistants is exciting and will keep expanding -- the smart virtual assistant market is estimated to grow at a CAGR of more than 26 % to reach over $12 billion U.S. dollars by 2024.
The Baltimore Ravens NFL American football team has introduced FlockBot, a new virtual assistant that gives fans the chance to ask questions about M&T Bank Stadium. FlockBot – which the Ravens stressed is not a real person – will be contactable 24 hours a day, seven days a week. The service will be accessible through the Ravens Mobile app and via the Contact Us page on the team's official website. Fans will be able to ask FlockBot what time M&T Bank Stadium opens on a specific game day, or where they can find a specific food item at the venue. The service will give an immediate response and, if necessary, connect fans to a real person who can provide extra information.
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Today marked the kickoff of Xiaomi's annual Mi Developer conference in Beijing, and the tech giant wasted no time in announcing updates across its AI portfolio. It took the wraps off the latest release of Mobile AI Compute Engine (MACE), its open source machine learning framework, and it demoed an improved version of its Xiao AI voice assistant (Xiao AI 3.0). Xiao AI, which Xiaomi says is used by 49.9 million users each month, will soon support multi-turn conversations à la Alexa Conversations and Google's Continued Conversation. This will be enabled on select phones, including the Xiaomi Mi 9 Pro and the Xiaomi Mi 9 via a software update, and it will allow for interruptions of the assistant at any time with new requests or commands. Xiao AI 3.0 also boasts improved voice shortcut functionality and a voice reply feature that will let users respond to incoming calls with transcribed text messages.
Being able to spell, checking your profile for typos and using correct grammar could determine whether you get a match on a dating site, a new study has revealed. Researchers worked with members of an online dating service and asked them to read fake profiles that had language errors as well as ones that had no mistakes. The study of more than 800 people on a dating site in the Netherlands found that errors such as writing'teh' for'the' and putting capital letters in the wrong place suggested sloppiness and a lack of attention to detail. If a profile has spelling mistakes and grammatical errors they were more likely to be perceived as less intelligent and so were less likely to be a match. 'In the case of online dating, inattentiveness can be interpreted as a lack of effort and interest in putting time and effort in constructing a dating profile.
In the formative years of a digital transformation journey, customer experience is the primary source of derived business value, as organizations see value in deploying strategic digital initiatives to augment and improve every customer interaction, with the goal of increasing customer growth and retention. Customer experience is followed closely by cost reduction, as organizations are continuously looking for opportunities to leverage technologies for increasing process efficiency, improving decision making, and automating more tasks. "As per a recent Gartner survey, by 2020, at least 40% of people will interact primarily with people-literate technologies, removing much of the perceived need to invest further in improving computer literacy. Additionally, virtual private assistants (VPAs) and voice response systems, such as Alexa, Cortana, Google Assistant, and Siri, are increasingly becoming the norm for consumer interaction with search engines, along with many other services that would previously have required interaction via web browsers." In the subsequent section, we will go through a few use cases that are now being increasingly deployed across industries to unlock untapped customer value.