Did you miss a session at the Data Summit? What do you need to do to increase the data literacy of your organization? In a world where your personal data (and the preferences and biases buried in that data) are used to influence your behaviors, beliefs, and decisions, data literacy is a fundamental and indispensable skill. And it's not just corporations that need this training. Data Literacy should be taught in universities, in high schools, in middle schools and even in adult education and nursing homes.

Autonomous vehicles are starting to become a real possibility in some parts of industry. Agriculture, transportation and military are some of the examples. The day when we are going to see autonomous vehicles in everyday life for the regular consumer is quickly approaching. Many of the operations that vehicles have to perform are based on sensor information and some AI algorithms. Vehicles need to collect data, plan their trajectory and execute the trajectory.

Welcome (or welcome back!) to the AI for social good series! In the second part, of this two-part series of articles, we will look at how Artificial intelligence (AI) coupled with the power of open-source tools and techniques like deep learning can help us further the quest for finding extra-terrestrial intelligence! In the first part of this two-part series, we formulated our key objective and motivation behind doing this project. Briefly, we were looking at different radio-telescope signals simulated from SETI (Search for Extra-terrestrial Intelligence) Institute data. We leveraged techniques to process, analyze and visualize radio signals as spectrograms, which are basically visual representations of the raw signal.

It is undeniable that our lives have been made better by artificial intelligence (AI). AI technology allow us to get almost anything, anytime, anywhere in the world at the click of a button; prevent disease epidemics and keep them from spiralling out of control, and generally just make day-to-day life a bit easier by helping us to save energy, book a babysitter, manage our cash and our health all at a very low cost. AI's penetration into systems and processes in virtually all sectors of business and life has been rapid and global. The speed and scale at which AI is proliferating does however raise the question of how at-risk we may be that the AI we are building for good can also be introducing damaging bias at scale. In this two-part series, I explore the issues with AI constructs, the good bad and the ugly and how we can think about shaping a future through AI in financial services that helps lift people up rather than scaling problems up.

This is the second in a two-part series of articles about recruiting trends for 2018. This installment addresses data analytics and artificial intelligence. Advances in talent data analytics and artificial intelligence (AI) will provide talent acquisition professionals in 2018 with the tools they need to be more strategic and insightful when making hiring decisions and streamline the transactional side of recruiting. Over 9,000 recruiters and hiring managers across the globe identified these trends, among others, as being the most impactful when surveyed by LinkedIn for the professional networking site's Global Recruiting Trends 2018 report. LinkedIn found that most companies are already using data to some degree to solve talent issues and that most recruiting professionals expect AI will eventually transform their roles.

And how can businesses, as well as members of the public, best keep themselves informed about the extent to which advances in AI may impact on the economy, as well as our society? A recent consultation by the UK House of Lords Select Committee on Artificial Intelligence has called for evidence on the economic, ethical and social implications of advances in artificial intelligence [call for evidence PDF]. The consultation poses a range of questions in particular topic areas, such as the impact of AI on society and the public perception of it, as well as ethical considerations and the role of the governemnt in responding to AI's development and use. For example, one question, targeted at experts in the field, asks "What is the current state of artificial intelligence and what factors have contributed to this?". Another, that could be answered by a much wider audience, seeks to explore the extent to which "efforts [should be] be made to improve the public's understanding of, and engagement with, artificial intelligence" and how they should be pursued.

In this two-part series, we will explore text clustering and how to get insights from unstructured data. It will be quite powerful and industrial strength. The first part will focus on the motivation. The second part will be about implementation. This post is the first part of the two-part series on how to get insights from unstructured data using text clustering.

In this two-part series, we will explore text clustering and how to get insights from unstructured data. It will be quite powerful and industrial strength. The first part will focus on the motivation. The second part will be about implementation. This post is the first part of the two-part series on how to get insights from unstructured data using text clustering.