United States Transportation Secretary Sean Duffy says there are concerns about the use of artificial intelligence to set personalised airline prices, echoing red flags brought up by three Democratic senators. Duffy on Tuesday promised to investigate any airline that uses the technology to set prices. "To try to individualise pricing on seats based on how much you make or don't make or who you are, I can guarantee you that we will investigate if anyone does that," Duffy said. "We would engage very strongly if any company tries to use AI to individually price their seating." Duffy noted Delta clarified that it would not use AI for pricing individual tickets, "and I'll take them at face value."

To enable the transition from fossil fuels towards renewable energy, the low-voltage grid needs to be reinforced at a faster pace and on a larger scale than was historically the case. To efficiently plan reinforcements, one needs to estimate the currents and voltages throughout the grid, which are unknown but can be calculated from the grid layout and the electricity consumption time series of each consumer. However, for many consumers, these time series are unknown and have to be estimated from the available consumer information. We refer to this task as scenario generation. The state-of-the-art approach that generates electricity consumption scenarios is complex, resulting in a computationally expensive procedure with only limited interpretability. To alleviate these drawbacks, we propose a fast and interpretable scenario generation technique based on predictive clustering trees (PCTs) that does not compromise accuracy. In our experiments on three datasets from different locations, we found that our proposed approach generates time series that are at least as accurate as the state-of-the-art while being at least 7 times faster in training and prediction. Moreover, the interpretability of the PCT allows domain experts to gain insight into their data while simultaneously building trust in the predictions of the model.

The way you think about a problem and the conceptual process you go through to find a solution may be guided by your personal skills or the type of problem at hand. Many mental models exist representing a variety of thinking patterns -- and as a Data Scientist, appreciating different…

I've been thinking a lot lately about how technology has become the cure-all elixir, with its increasingly important, and sometimes problematic, role it plays in our lives. This line of thinking was in large part spurred by The Future of Digital Disruption event we co-hosted last month with Oxford University's Saïd Business School. The event was co-moderated by Professor Andrew Stephen from Oxford's Said Business School and Teradata's Martin Willcox, VP Technology (EMEA). Leaders from Audi, Barclays, Kantar, Sony Music, O2 Czech Republic, Facebook, MMA, WPP, Walmart, Teradata and others, as well as leading faculty and researcher's from Oxford's Said Business School Future of Marketing Initiative shared experiences and insights about some of the most complex issues facing leaders today, with a focus on challenges at the intersection of marketing and technology (e.g., analytics, AI, machine learning) and identifying new ways to achieve business growth enabled by technology. The keynote sessions and panel conversations were engaging and varied to encompass the dense topic of how digital disruption will shape the future.

Through the increased availability of data and online connectivity through novel interfaces & APIs, we are faced with more opportunities than ever before. For instance, today, you can use many services to get data on purchases you'd like to make and suggestions on when the optimal time to make the purchase would be (e.g. However, soon, this operation may seem antiquated as artificial intelligence (AI) and assisting algorithms have become more prevalent and can make these decisions in your place. In imagining a future like this, will the balance of power shift toward the data owner and end-purchaser or will tool manufacturers and conduits be able to gain an upper hand? With consumer preferences for regained privacy and control, as well as new regulation such as the General Data Protection Regulation (GDPR), it's plausible to see more data held by the consumer and the consumer exercise more control over where their data is used.

AI-driven personalised marketing holds the key to winning and retaining consumers in the digital age. The formula to acquire customers in today's hyper-connected online and offline communication ecosystem, can be summarised through the following phrase: "right audience, right channel, right time." Moreover, this phrase even encapsulates what personalised marketing is all about. Simply put, it is the art of creating and delivering communication tailored according to each individual consumer's preferences. Fundamentally, personalised marketing is the process of communicating the different value of the same product or service to various consumer segments, be it students, working professionals, millennials, middle-aged consumers, digital or offline consumers, etc.

Premise: How will the traditional car industry create and extract customer value in the future when the source of that value is no longer the vehicle itself? An increasingly digital economy is overwhelming every industry, and no business, from the largest legacy institutions to plucky start-ups, is safe. To survive, businesses must embrace digital transformation. For those who haven't, we have already seen what happens to them. Once long-standing giants in advertising, marketing, commerce, entertainment, transportation and hospitality industries have either shuttered their doors for good, or are on the fringes of the industries they once dominated (see Figure 1).

Artificial Intelligence (AI) and machine learning will improve sales and marketing by enabling processes and communication without continuous direction. The addition of voice-first systems could eliminate much of the power of'push marketing'. Subscribe to The Financial Brand via email for FREE!Marketing and advertising have been around since the dawn of the Sumerian culture over 6,000 years ago. Marketing methods will be fundamentally altered with the rise of artificial intelligence, chatbots and the emergence of voice-first communication systems. Cloud computing provides an exponential increase in processing power, while advanced analytics has provided new ways to move from data to insight.

Say artificial intelligence (AI) and your first thought may be of futuristic robots, but the future may actually be closer than you think. Whether it's voice activated home assistants or internet connected cars – and machine learning is getting better, and more accessible every day. For the past decade companies and marketers have been moving towards marketing automation and nowhere is that potential greater than with AI technology. Powerful new possibilities are emerging, allowing marketers to deliver more personal and relevant messaging at a greater scale, made possible by AI. Seven out of 10 marketing decision-makers are already implementing AI-powered technologies, or at least have concrete plans to do so (KRC Research).

Machine learning is more popular in the travel industry now than ever. There's a simple explanation for that fact: machine learning is more powerful now than ever before. The appeal of machine learning – essentially a form of artificial intelligence (AI) whereby computers learn without being explicitly programmed with new information – is clear. At exceptional speed, for example, complex algorithms can identify subtle but important data patterns that humans could never have spotted. In'learning' from that information, the'machine' can predict patterns ahead, and then act to process that knowledge to maximise future business.