Beginning as early as next year, many people are expected to have more conversations with digital voice assistants than with their spouse. Presently, the vast majority of these assistants--from Amazon's Alexa to Microsoft's Cortana--are projected as female, in name, sound of voice and'personality'. 'I'd blush if I could', a new UNESCO publication produced in collaboration with Germany and the EQUALS Skills Coalition holds a critical lens to this growing and global practice, explaining how it: The title of the publication borrows its name from the response Siri, Apple's female-gendered voice assistant used by nearly half a billion people, would give when a human user told'her', "Hey Siri, you're a bi***." Siri's submissiveness in the face of gender abuse – and the servility expressed by so many other digital assistants projected as young women – provides a powerful illustration of gender biases coded into technology products, pervasive in the technology sector and apparent in digital skills education. According to Saniye Gülser Corat, UNESCO's Director for Gender Equality, "The world needs to pay much closer attention to how, when and whether AI technologies are gendered and, crucially, who is gendering them."

"It sounded very real," Mr. Tran said in an interview after hanging up the call with Google. Google later confirmed, to our disappointment, that the caller had been telling the truth: He was a person working in a call center. The company said that about 25 percent of calls placed through Duplex started with a human, and that about 15 percent of those that began with an automated system had a human intervene at some point. We tested Duplex for several days, calling more than a dozen restaurants, and our tests showed a heavy reliance on humans. Among our four successful bookings with Duplex, three were done by people.

One of the most interesting demos at this week's Google I/O keynote featured a new version of Google's voice assistant that's due out later this year. A Google employee asked the Google Assistant to bring up her photos and then show her photos with animals. She tapped one and said, "Send it to Justin." The photo was dropped into the messaging app. From there, things got more impressive.

From personal assistants to legal counsel on parking fines, artificial intelligence (AI) and machine learning (ML) have established their potential as disruptive technology that will alter industries. With each passing day, further discoveries enable AI to become more sophisticated and viable in our world. Naturally, like all things digital, AI has had a profound impact on digital marketing as well. From Google's RankBrain search engine algorithm to Amazon's personalized recommendations, it is powering the world's leading organizations and changing the face of the modern digital marketing landscape. Currently, I work as senior vice president of marketing at CUJO AI, an AI-driven network security and intelligence company.

Assigning female genders to digital assistants such as Apple's Siri and Amazon's Alexa is helping entrench harmful gender biases, according to a UN agency. Research released by Unesco claims that the often submissive and flirty responses offered by the systems to many queries – including outright abusive ones – reinforce ideas of women as subservient. "Because the speech of most voice assistants is female, it sends a signal that women are obliging, docile and eager-to-please helpers, available at the touch of a button or with a blunt voice command like'hey' or'OK'," the report said. "The assistant holds no power of agency beyond what the commander asks of it. It honours commands and responds to queries regardless of their tone or hostility. In many communities, this reinforces commonly held gender biases that women are subservient and tolerant of poor treatment."

Google Assistant can draw on voice command, as seen here at the Google I/O conference in 2018, with the help of machine learning techniques. Artificial intelligence systems powered by machine learning have been creating headlines with applications as varied as making restaurant reservations by phone, sorting cucumbers, and distinguishing chihuahuas from muffins. Media buzz aside, many fast-growing startups are taking advantage of machine learning (ML) techniques like neural networks and support vector machines to learn from data, make predictions, improve products, and enhance business decisions. Unfortunately "machine learning theater" – companies pretending to use the technology to make theirs seem more sophisticated for a higher valuation – is also on the rise. Undeniably, ML is transforming businesses and industries, with some more likely to benefit than others.

We have all read market predictions describing billions of devices and the hundreds of billions dollars in profit that the Internet of Things (IoT) promises.a Security and the challenges it represents27 are often highlighted as major issues for IoT, alongside scalability and standardization. In 2017, FBI Director James Comey warned, during a senate hearing, of the threat represented by a botnet taking control of devices owned by unsuspecting users. Such a botnet can seize control of devices ranging from connected dishwashers,b to smart home cameras and connected toys, not only using them as a platform to launch cyber-attacks, but also potentially harvesting the data such devices collect. In addition to concerns about cyber-security, corporate usage of personal data has seen increased public scrutiny. A recent focus of concern has been connected home hubs (such as Amazon Alexa and Google Home).c

According to recent and separate studies from Gartner, Harvey Nash/KPMG, and O'Reilly, somewhere between 24% and 37% of organizations are at least moderately investing in machine learning and artificial intelligence. Much of this will be AI/ML embedded in applications like chatbots, recommendation engines, and virtual assistants and some consider RPAs a form of AI/ML. But it also means that more organizations are testing AI/ML on their proprietary data, developing models, and connecting models to their end user applications. The most advanced organizations using AI/ML like Twitter and Facebook are developing entire model development lifecycles to support ongoing model improvements are retraining. Integrating Applications with Machine Learning Models As a full stack developer or a solutions architect, it's quite likely that you'll be asked to integrate applications and data pipelines to ML models.

Artificial Intelligence is a technology solution with the power to change the world. Once the sole property of sci-fi writers and creative minds, artificial intelligence is now an increasingly common part of our professional and personal lives. We make purchases through virtual assistants hooked up to our phones and speakers. Our bots remind us when we have appointments and help us to manage our schedule. In the business world, artificial intelligence even has the potential to take care of mundane tasks on our behalf, freeing up more time for us to be as intuitive and innovative as we like.

Artificial Intelligence is a technology solution with the power to change the world. Once the sole property of sci-fi writers and creative minds, artificial intelligence is now an increasingly common part of our professional and personal lives. We make purchases through virtual assistants hooked up to our phones and speakers. Our bots remind us when we have appointments and help us to manage our schedule. In the business world, artificial intelligence even has the potential to take care of mundane tasks on our behalf, freeing up more time for us to be as intuitive and innovative as we like.