AI News, Timeline of artificial intelligence

Machine Learning / Artificial Intelligence

AI changing every aspect of our lives in the next 10 years through automating and optimizing processes such as self-driving vehicles, online recommendations on Netflix and Amazon, fraud detection in banks, image and video recognition, natural language processing, question answering machines (e.g., IBM Watson) and many more.

diagnosis in medical imaging, analysing the deluge of healthcare data, drug discovery, robotic surgery and personalised medicine for example. This

The Role Of AI In Customer Experience

In this post, I will lay out why artificial intelligence is a game changer in CX, take a look under the hood at how AI is applied to CX, and explore use cases for how leading edge companies are already reaping benefits from AI applications in customer experience.

Salespeople, call center agents and employees in other customer-facing roles cannot be expected to understand a customer’s entire history and derive their own insights from it in real time.

Customer journey analytics platforms provide this service for a fraction of the cost of the dedicated data services providers of yore—even delivering a level of data integration free of charge.

The truth is that, in addition to elegant SaaS data streams, most enterprises must rely on myriad on-site, home-grown and legacy touchpoint data sources—product interfaces, payment platforms, point-of-sale systems, customer care, etc..

Customer journey analytics platforms are now filling this gap with a host of APIs options and development kits to deliver comprehensive, real-time touchpoint integration with minimal investment.

By context, I mean more than simply designating a certain interaction as an “inbound call” and another as “order fulfillment.” AI must know the significance of these events in shaping a customer behavior.

That requires an awareness of both the journey that these touchpoints helped to shape and the KPIs which were subsequently impacted by that customer behavior—whether related to revenue, profitability, customer lifetime value, customer satisfaction or other factors driving high-level business performance.

With proper business context, an AI can find touchpoints and tactics which actually shape the customer behaviors behind the business’s primary measures of performance.

Now that we understand what it takes to successfully apply artificial intelligence in customer experience, let’s delve into some of those applications to see how AI is unleashing disruption across various aspects of customer experience by unifying data, providing insights in real-time, and incorporating critical business context.

As I previously mentioned, salespeople, call center agents and employees in other customer service roles cannot be expected to ingest and understand a customer’s entire history prior to each conversation.

Mining insights across billions of unique customer journeys using traditional analytics methods and tools is a laborious and slow process, which tends to confine it’s usage to a small set of pre-defined problems.

The power of AI-enabled customer journey analytics is that it can sift through a much, much larger and more complex data space and thereby uncover many more business opportunities—even opportunities you didn’t realize you should look for.

Artificial intelligence-enabled customer journey analytics can find answers to important CX queries like: Leading companies are constantly experimenting to determine the best way to employ AI to improve customer experience.

These companies have unified disparate customer data sources, analyzed end-to-end customer journeys and are using machine learning algorithms to predict future customer behavior.

Nordea also partnered with an AI-based text analytics solution provider to interpret hundreds of inbound customer communications per second and intelligently forward them to the right business unit.

Sephora has thoughtfully considered the entire customer journey—the Visual Artist tool ties in to Sephora’s entire inventory of products seamlessly, and driven by the AI engine, personalized recommendations and offers are made in real-time.

They use sophisticated analytics to glean insights from a customer’s purchasing history, and combine it with weather conditions and other relevant data to make product recommendations in real-time.

AI presents an opportunity to turn many-siloed, multi-channel enterprises into singular “personas” who remember, understand, and respond to their customers’ achievements and setbacks in a meaningful way.

Most companies find it difficult, if not impossible, to accomplish those tasks on their own, given the dearth of data scientists, the fact that disparate systems are not AI ready, and the need to rapidly build new systems, apps, and capabilities.

Timeline Of Artificial Intelligence

Humor from The Onion: The Week In Pictures

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Trump’s executive order on AI, explained

President Donald Trump released an executive order on Monday that laid out a broad plan — but no new funding — for how the US will get ahead on artificial intelligence.

It’s a far-reaching plan that focuses on not just technological development but also progress in related areas — including government regulation, education, private-public sector data sharing, and international diplomacy.

It states that the US must “drive technological breakthroughs in AI” to “promote scientific discovery, economic competitiveness, and national security.” Trump’s AI plan asks federal agencies to prioritize research in the field by reallocating resources within their existing budgets, calling on the heads of federal agencies to “consider appropriate administrative actions” to do so.

Lynne Parker, the assistant director for artificial intelligence at the White House Office of Science and Technology Policy, who helped work on the executive order, responded to this criticism in a statement, saying in part, “With the coordination and accountability directed by the Initiative, federal agencies can better put to use the dollars appropriated to them by Congress to ensure American AI leadership, as well as identify the barriers that currently impede AI R&D.” Furman, who worked on the AI task force under the Obama administration, appears skeptical.

Tech giants like Google, Apple, Microsoft, and Amazon, to name just a few, should welcome this potential treasure trove of wide-reaching government data that is necessary to train AI algorithms to become as smart as humans — or smarter.

The executive order, while it doesn’t address these concerns directly, does contain the phrase “civil liberties” five times, and lays out a section and timeline for developing potential federal policy around regulating AI.

The order calls for leaders at the Office of Management and Budget, the Office of Science and Technology Policy, the Domestic Policy Council, and the National Economic Council to draft a memo within 180 days of the order’s release that advises setting guidelines for the AI sector that will “advance American innovation while upholding civil liberties, privacy, and American values.” Federal agencies with regulatory power will consider enacting the proposals in the forthcoming memo.

Again, the agenda here lacks specifics, broadly calling for agencies that provide educational grants to “consider AI as a priority area within existing Federal fellowship and service programs,” including at the high school and university level.

Again, the plans here are vague — calling for the US to “promote an international environment that supports American AI research and innovation.” The document calls on the assistant to the president for national security affairs, the Office of Science and Technology Policy, and others to come up with an action plan around this.

Most of the goals stated in this executive order — increase AI development, set guidelines for regulation, train the workforce — are broadly popular, but how feasible they are without any additional plan for funding is a different question.

But without knowing more about what funding for Trump’s AI initiative will look like, it’s hard to say that it will be able to deliver all that it aims — to cement the US ahead of China as the responsible leader in one of the most important technologies of our time.

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