In December 2020 we launched a focus series AI for Good: UN sustainable development goals (SDGs). Each month we pick a different sustainable development goal (SDG) and highlight work in that area. February was the turn of UN SDG number 13: climate action. In this summary article we highlight some of work at the intersection of AI and climate science. Climate Change AI (CCAI) is a volunteer-led effort bringing together people from academia, industry, and the public sector.

Summary contributed by Alexandrine Royer, administrative coordinator at The Foundation for Genocide Education. Mini-summary: Although it may not always seem evident, the development of AI technologies is a part of the patterns of power that characterize our intellectual, political, economic and social worlds. Recognizing and identifying these patterns is essential to ensure that those at the bottom of society are not disproportionately affected by the adverse effects of technological innovation. To protect and prevent harm against vulnerable groups, the authors recommend adopting a decolonial critical approach in AI to gain better foresight and ethical judgement towards advances in the field. They offer three tactics that can lead to the creation of decolonial artificial intelligence: creating a technical practice for AI, seeking reverse tutelage and reverse pedagogies and the renewal of affective and political communities.

These past few months have been especially challenging, and the deployment of technology in ways hitherto untested at an unrivalled pace has left the internet and technology watchers aghast. Artificial intelligence has become the byword for technological progress and is being used in everything from helping us combat the COVID-19 pandemic to nudging our attention in different directions as we all spend increasingly larger amounts of time online. It has never been more important that we keep a sharp eye out on the development of this field and how it is shaping our society and interactions with each other. With this inaugural edition of the State of AI Ethics we hope to bring forward the most important developments that caught our attention at the Montreal AI Ethics Institute this past quarter. Our goal is to help you navigate this ever-evolving field swiftly and allow you and your organization to make informed decisions. This pulse-check for the state of discourse, research, and development is geared towards researchers and practitioners alike who are making decisions on behalf of their organizations in considering the societal impacts of AI-enabled solutions. We cover a wide set of areas in this report spanning Agency and Responsibility, Security and Risk, Disinformation, Jobs and Labor, the Future of AI Ethics, and more. Our staff has worked tirelessly over the past quarter surfacing signal from the noise so that you are equipped with the right tools and knowledge to confidently tread this complex yet consequential domain.

With the latest advances in technology, you can tap into a massive audience using all sorts of online and offline channels. Without the right tools, it's nearly impossible to figure out how and where to focus your marketing efforts. Automation makes marketing a lot less complex and exhausting. Implementing machine learning technologies alongside your marketing solutions will help you fully understand which customers respond to which techniques – emails, free e-books, Facebook ads, etc. Additionally, it enables you to deliver a more personalized user experience. If this in-depth educational content on using AI in marketing is useful for you, you can subscribe to our Enterprise AI mailing list to be alerted when we release new material.

What comes to your mind when you think of AI-driven personalization in retail and commerce? Do salespeople recognize you the minute you walk into the store and give recommendations based on your purchase history? Perhaps the dressing rooms are equipped with smart displays which show you complementary products to the outfits you've already chosen to try on? Maybe a conversational bot alerts you even before you decided to go shopping that your favorite brand of wine is in stock again and available on aisle 12? We might achieve these futuristic-sounding goals in 5 years or so, but you also need to understand what's actually possible today with AI-personalization of your customer experience. What are the challenges that retail stores and e-commerce companies need to overcome to truly personalize their customers' experience?

News Analysis: America In An @RealDonaldTrump Era – Everything International Clients Need To Know PESTEL Part 1. November 10, 2016

Prospects of universal AI ethics seem slim. However the five design pillars will serve organizations well beyond the social fads and fears. The goal – build controls that will identify biases, show attribution, and enable course correction as needed. Ready to roll out your plans for AI? Do you understand the business model implications? Who will you partner with for AI? Add your comments to the blog or reach me via email: R (at) ConstellationR (dot) com or R (at) SoftwareInsider (dot) org. Please let us know if you need help with your Digital Business transformation efforts. Here's how we can assist: Reprints can be purchased through Constellation Research, Inc. To request official reprints in PDF format, please contact Sales .

Over the past four decades, valiant attempts at personalization have failed due to the lack of relevant and intelligent automation. Moreover, expectations of consumers and prospects have only grown. Currently, the fashionable approach is predictive. Prediction does a great job of using past history to foretell future patterns. If one knows a person always gets a specific type of coffee at the same time every day, that's predictive.

In an age of digital disruption, customers, partners, suppliers, and employees have grown accustomed to massive market choice, a plethora of pricing and policy options, and convenient delivery. The rise in expectations creates an insatiable cycle of satisfaction and disappointment that an omni-channel approach alone cannot deliver. Today, omni- channel plays only a temporary role as organizations must progress forward. Lack of relevance leads to lack of engagement. Contextual relevancy can be correlated to an immediate effect on the top line. Constellation estimates that lack of content relevancy often results in 83 percent lower response rates in the average marketing campaign.

As artificial intelligence (AI) continues to move from the summer of hype to the fall tech conference news cycle, mass confusion has begun on what AI can be used for. From fears of SKYNET, to hopes for the computer in StarTrek and Jarvis in Iron Man, the value will come from defining the proper outcomes. AI is more than just a fad. With a market size of $100B by 2025, Constellation sees the AI subsets of machine learning, deep learning, natural language processing, and cognitive computing taking the market by storm (see Figure 1). The disruptive nature of AI comes from the speed, precision, and capacity of augmenting humanity. Perception describes what's happening now. The first set of outcomes rudimentary describe surroundings as manually programmed. Notification tells you what you asked to know. Notifications through alerts, workflows, reminders, and other signals help deliver additional information through manual input and learning. Suggestions build on the past behaviors and ...