User Centered Design (UCD) - diverse and inclusive teams are key to AI solutioning success. This blog is a continuation of the Building AI Leadership Brain Trust Blog Series which targets board directors and CEO's to accelerate their duty of care to develop stronger skills and competencies in AI in order to ensure their AI programs achieve sustaining results. In this blog series, I have identified forty skill domains in an AI Leadership Brain Trust Framework to guide board directors and CEO's to ensure they can develop and accelerate their investments in successful AI initiatives. You can see the full roster of the forty leadership Brain Trust skills in my first blog. Each of the blogs in this series explores either a group of skills or does a deep dive into one of the skill areas.

Whether it's police brutality, the disproportionate over-exposure of racial minorities to COVID-19 or persistent discrimination in the labour market, Europe is "waking up" to structural racism. Amid the hardships of the pandemic and the environmental crisis, new technological threats are arising. One challenge will be to contest the ways in which emerging technologies, like Artificial Intelligence (AI), reinforce existing forms of discrimination. From predictive policing systems that disproportionately score racialised communities with a higher "risk" of future criminality, all the way to the deployment of facial recognition technologies that consistently mis-identify people of colour, we see how so called "neutral" technologies are secretly harming marginalised communities. The use of data-driven systems to surveil and provide a logic to discrimination is not novel.

No wonder, Artificial Intelligence is the future. We've seen its application in possibly every field now. The problem isn't with the technology, it is with the biasness that goes in, says Timnit Gebru. She goes on to add that it is built in a manner that replicates the white work force that's mostly men-dominated making it. Right from her first lecture in Spain which is by far the world's most important conference on AI till date, she has seen a vast difference in the number of men and women, obviously men being dominant in number.

AI is facing several critical challenges. Not only does it need huge amounts of data to deliver accurate results, but it also needs to be able to ensure that data isn't biased, and it needs to comply with increasingly restrictive data privacy regulations. We have seen several solutions proposed over the last couple of years to address these challenges -- including various tools designed to identify and reduce bias, tools that anonymize user data, and programs to ensure that data is only collected with user consent. But each of these solutions is facing challenges of its own. Now we're seeing a new industry emerge that promises to be a saving grace: synthetic data.

This paper addresses the interesting problem of processing and analyzing data in geographic information systems (GIS) to achieve a clear perspective on urban sprawl. The term urban sprawl refers to overgrowth and expansion of low-density areas with issues such as car dependency and segregation between residential versus commercial use. Sprawl has impacts on the environment and public health. In our work, spatiotemporal features related to real GIS data on urban sprawl such as population growth and demographics are mined to discover knowledge for decision support. We adapt data mining algorithms, Apriori for association rule mining and J4.8 for decision tree classification to geospatial analysis, deploying the ArcGIS tool for mapping. Knowledge discovered by mining this spatiotemporal data is used to implement a prototype spatial decision support system (SDSS). This SDSS predicts whether urban sprawl is likely to occur. Further, it estimates the values of pertinent variables to understand how the variables impact each other. The SDSS can help decision-makers identify problems and create solutions for avoiding future sprawl occurrence and conducting urban planning where sprawl already occurs, thus aiding sustainable development. This work falls in the broad realm of geospatial intelligence and sets the stage for designing a large scale SDSS to process big data in complex environments, which constitutes part of our future work.

Experts advocate robust regulation of facial recognition technology to reduce discriminatory outcomes. After Detroit police arrested Robert Williams for another person's crime, officers reportedly showed him the surveillance video image of another Black man that they had used to identify Williams. The image prompted him to ask the officers if they thought "all Black men look alike." Police falsely arrested Williams after facial recognition technology matched him to the image of a suspect--an image that Williams maintains did not look like him. Some experts see the potential of artificial intelligence to bypass human error and biases.

"What is your customer acquisition strategy?" is a typical question for startups. And many of the 40 companies pitching in eight categories during the 13th annual SXSW Pitch Event showed they had a clear roadmap for attracting ideal customers to grow their businesses. A few highlights from this year's incredible group of SXSW Pitch finalist include: Using XR, holoride takes everyday car rides and transforms them into hyper-immersive experiences by capturing the real-time physical feedback of the vehicle you're in, making every journey fun for children and adults. If you're behind the wheel, MicroTraffic makes it safer to drive by measuring near-misses at intersections with AI technology. Other companies aim to help often overlooked populations.

If you say the word "green activist" to a corporate executive, Greta Thunberg may spring to mind -- and provoke fear. Today, however, there is another force to watch: robots. Consider an artificial intelligence-enabled platform called "ClimateBert". This was recently created by Swiss and German academics to parse the accounts of 800 businesses backing the "task force for climate related financial disclosure", principles pioneered by Mark Carney, former Bank of England governor. It sounds (and is) geeky.

Biometric surveillance is coming for you, even if you have'nothing to hide' Clare Garvie is a Senior Associate at Georgetown University's Center on Privacy and Technology, where she has dedicated her work to studying law enforcement's use of face recognition technology on the American public. She is considered the foremost expert on face recognition technology; last year she testified in front of Congress. She writes extensively on its use in law enforcement investigations. As well, she brings to light the worrying ways the technology disrupts privacy, circumvents judicial norms and legal precedents, and promotes chilling effects on free speech and civil liberties. All of this happens under a veil of secrecy, without public consent and largely outside of the purview of American lawmakers. Garvie's research spotlights the ways these technologies are disproportionately used on Black and Brown communities and the failures of face recognition algorithms when deployed on people of color and women. The technology's efficacy, already cause for concern, is further problematized by law enforcement's cavalier practices.

In Sales, Planning & Analytics, we are a highly collaborative team at the nexus of every department in the organization. We lead analysis for profit generating for our high quality video games to traditional retail customers in the Americas and digital retail customers worldwide. Our SPA group synthesizes data from a variety of internal and external sources to help drive business and lifecycle planning that helps to position Take-Two as best in class. Take-Two Interactive Software, Inc. is a leading developer, publisher, and marketer of engaging entertainment for consumers around the globe. We've built arguably the most critically acclaimed and commercially successful entertainment experiences around the world.