NARRATOR: The future unfolds before our eyes, but is it always beyond our grasp? What was once the province of the gods has now come more clearly into view, through mathematics and data. Out of some early observations about gambling, arose tools that guide our scientific understanding of the world and more, through the power of prediction. BOATSWAIN'S MATE 1 LUKE SCHAFFER (United States Coast Guard): Keep a good look out. NARRATOR: …every day mathematics and data combine to help us envision what might be. LIBERTY VITTERT (University of Glasgow): It's the best crystal ball that humankind can have. NARRATOR: Take a trip on the wings of probability, into the future. MONA CHALABI (The Guardian, United States Edition): We are thinking about luck or misfortune, but they just, basically, are a question of math, right? The Orange County Fair, held in Southern California: in theory, these crowds hold a predictive power that can have startling accuracy, but it doesn't belong to any individual, only the group. And even then, it has to be viewed through the lens of mathematics. The theory is known as the "wisdom of crowds," a phenomenon first documented about a hundred years ago. Statistician Talithia Williams is here to see if the theory checks out and to spend some time with the Fair's most beloved animal, Patches, a 14-year-old ox. TALITHIA WILLIAMS (Harvey Mudd College): It was a fair, kind of like this one, where, in 1906, Sir Francis Galton came across a contest where you had to guess the weight of an ox, like Patches, you see here behind me. NARRATOR: After the ox weight-guessing contest was over, Galton took all the entries home and analyzed them statistically. To his surprise, while none of the individual guesses were correct, the average of all the guesses was off by less than one percent. But is it still true? TALITHIA WILLIAMS: So, here's how I think we can test that today. What if we ask a random sample of people, here at the fair, if they can guess how many jellybeans they think are in the jar, and then we take those numbers and average them and see if that's actually close to the true number of jellybeans?
Three-quarters of developers think those who create artificial intelligence (AI) algorithms are ultimately responsible for AI's impact on society, according to a global survey. Every conference this year contains a dead human genius reincarnated as software system or a robot. Yes, there is a lot of hype, but there is real worth in AI and Machine Learning. Read our counseling on how to avoid adopting "black box" approach. You forgot to provide an Email Address.
Once upon a time, surveys were a staple for every leader to solicit feedback and every company to assess engagement. But now, surveys are starting to look like diesel trucks collecting dust in the age of electric cars. Companies are using cool new machine-learning algorithms that crunch big data to measure employee engagement through email response times and network connections outside one's core team, and forecast turnover risk by tracking signals like how often employees update their resumes. Who needs a clunky, time-consuming survey where some employees only tell you what you want to hear, and others don't bother to respond at all? For decades, having regular employee opinion surveys has been on evidence-based lists of high-performance HR practices.
Although they've technically been around since the 1950s, virtual chatbots only recently became popularized, as brands implement them to reach more customers with greater efficiency. KLM Royal Dutch Airlines, for example, launched a chatbot via Facebook Messenger called "BB" (stands for BlueBot). The primary function of BB is to help passengers book tickets and keep them up to date on flight status, gate changes, and similar data-driven functions. The company built the chatbot to assist its human support team, which handles more than 16,000 customer interactions weekly, according to coverage on the MarTech Today blog. In just the first six months of operation, BB sent nearly two million messages to more than 500,000 customers.
According to a recent Teradata study, 80% of IT and business decision-makers have already implemented some form of artificial intelligence (AI) in their business. The study also found that companies have a desire to increase AI spending. Forty-two percent of respondents to the Teradata study said they thought there was more room for AI implementation across the business, and 30% said their organizations weren't investing enough in AI. Forrester recently released their 2018 Predictions and also found that firms have an interest investing in AI. Fifty-one percent of their 2017 respondents said their firms were investing in AI, up from 40% in 2016, and 70% of respondents said their firms will have implemented AI within the next 12 months.
ARTIFICIAL INTELLIGENCE (AI) is everywhere and it's as big a dent in cyberspace as it is in the real world. According to PwC's Global Consumer Insights Survey 2018, AI is making waves in the world of retail. "In some ways, AI is the future of retail," says the report. The report found that 45 percent of store operators intended to increase their use of AI within the next three years to transform their business, improving customer engagement boosting how customer insights are generated from social media. Globally, customers too are adopting AI tools in the home to improve their lifestyle and experience.
Almost a third (32%) of consumers surveyed globally by PwC plan to buy an AI device including robots or automated assistants, with retailers watching closely as'voice commerce' develops in the home. The findings are published today in PwC's Global Consumer Insights survey, which assesses the shopping behaviour, habits and expectations of over 22,000 consumers in 27 countries. The study reports that 10% of respondents already own artificial intelligence (AI) devices, such as robots and automated personal assistants like Amazon Echo or Google Home, and 32% said they plan to buy one. Both consumer and retailer habits and offerings still need time to adapt however, to make the most of the new voice commerce channel. Interest in the devices is strongest amongst consumers in emerging economies including China, Vietnam, Indonesia and Thailand.
A survey of early adopters helps correct some common misconceptions about artificial intelligence. Artificial intelligence (AI) is one of the most frequently discussed topics in business today, but even more than most new technologies, its promise is sometimes obscured by a set of lingering myths--particularly among those whose exposure to the technology has been limited. Professionals with first-hand experience have a different perspective, according to the 2017 Deloitte State of Cognitive Survey, which is based on interviews with 250 business executives who have already begun adopting and using AI and cognitive technologies. The responses of these early adopters shed considerable light on the current state of cognitive technology in organizations. Along the way, they help dispel five of the most persistent myths.
"Artificial intelligence is getting ready for business, but are businesses ready for AI?," asks McKinsey in a recently published report, Artificial Intelligence: the Next Digital Frontier. "AI adoption outside of the tech sector is at an early, often experimental stage," is the report's succinct answer. "Few firms have deployed it at scale." The report is based on a survey of over 3,000 AI-aware C-level executives across 10 countries and 14 sectors. Only 20% of respondents had adopted AI at scale in a core part of their business.