Advances in artificial intelligence (AI) are creating opportunities to improve K-12 education. Personalized learning applications can increase student engagement in the classroom and close learning gaps, while AI tools can help teachers reduce their workloads, design better interventions, and reduce burnout. But there are a number of technical, operational, and social challenges that stand in the way of widespread AI usage in schools. Moreover, policymakers have not yet embraced a strategic vision of AI to ensure effective deployment of the technology in the classroom. Join the Center for Data Innovation for a panel discussion about the ways policymakers can address existing concerns while supporting AI use by students, teachers, and administrators.

LONDON – A new law designed to regulate artificial intelligence in Europe could end up costing the EU economy 31 billion euros ($36 billion) over the next five years, according to a report from Washington-based think tank the Center for Data Innovation released on Sunday. The Artificial Intelligence Act -- a proposed law put forward by the European Commission, the executive arm of the EU -- will be the "world's most restrictive regulation of AI," according to the center. "It will not only limit AI development and use in Europe but impose significant costs on EU businesses and consumers," the organization said in the report. The commission said it disagrees with the findings of the report and that they appear to be flawed. The Center for Data Innovation argues that a small or mid-sized enterprise with a turnover of 10 million euros would face compliance costs of up to 400,000 euros if it deployed a high-risk AI system.

EU policymakers recently proposed a sweeping set of regulations called the Artificial Intelligence Act (AIA). If made law, the AIA would offer European citizens the strictest, most comprehensive protections against predatory AI systems on the planet. And big tech is terrified. Up front: The Center for Data Innovation published a report on Sunday titled "How Much Will the AIA Cost Europe?" Attend the tech festival of the year and get your super early bird ticket now!

In the coming years, there are few parts of daily life that artificial intelligence won't touch in one way or another, and the automotive sector is no exception. When it comes to vehicles, however, implementing AI will place enormous demands on data centre technology. Christian Ott, director of Solution Engineering at NetApp, explores how storage and compute can keep pace with the challenge. Usually, when you mention the idea of applying AI in the automotive sector to someone, their first thought is self-driving cars. In the current wave of research and development in autonomous vehicles (AVs), it's estimated that the leading thirty companies have invested $16 billion into building a car that can take itself from A to B, and, as we all know, that technology hasn't arrived just yet.

Artificial intelligence, blockchain and IoT devices are just a few of the tools that analysts and executives believe will play a huge role in the coming year. "For 2020, many organizations will augment or expand digital transformation efforts into digital innovation to drive business results. Digital transformation isn't going away and never will as long as there are ongoing opportunities for transformation," said Mark Troester, vice president of strategy at the technology development company Progress. SEE: Artificial intelligence: A business leader's guide (free PDF) (TechRepublic Premium) "Making digital innovation part of the fabric doesn't necessarily call for separate teams or big investments," Troester said. "It starts by developing a culture of innovation by grounding teams in objectives and their accountability for them, and then give them broad discretion to execute."

Government agencies requested $973.5 million in nondefense AI research spending for the fiscal year ending in September 2020. It is the first time the federal government has calculated agency-specific requests for spending on artificial intelligence. AI spending for the Defense Department is classified. Michael Kratsios, the U.S. chief technology officer, said at a Washington panel event that breaking down the government's AI spending will allow it to better identify investment opportunities, conduct strategic planning across different parts of the government and find collaboration opportunities with industry and academia. Trump administration officials said they believe the total reflects their commitment to maintaining and strengthening U.S. leadership in AI.

The United States Geological Survey confirmed with the Center for Data Innovation over email on July 22, 2019, that "1-meter DEMs are available or in progress for 45% of the country."

While the United States currently has an edge in the race to develop artificial intelligence, China is rapidly gaining ground as Europe falls behind, according to a report released today by the Center for Data Innovation. The study arrives amid a wide-ranging debate about which region has gained AI leadership, and the implications that holds for dominating cutting-edge technologies such as autonomous vehicles and other forms of automation. The winners of an AI arms race could hold a significant economic advantage in the decades to come. There has been growing concern among U.S. tech companies and policymakers that China's initiative to make it dominant in AI by 2030 is allowing it to dictate this critical field. The ability of its central government to allow sweeping data gathering and determine official champions to lead this charge seems to have given its efforts significant momentum.

The European Commission's Joint Research Center released a report that explores the European perspective on artificial intelligence (AI), along with the global AI landscape's state of play. The report recognizes the value of AI across industry, but while acknowledging the fierce competition on AI taking place between the EU, China, and the United States, it ultimately dismisses the need for Europe to win this global race, arguing instead that for the EU, the more important goal is focusing on developing values and ethics in AI. This is a naive perspective, especially given that China is not only fiercely competing on developing AI, but also aspiring to dominate in AI so as to compete in industries where Europe is leading today. Ironically, even if the EU's first priority is to shape the values and ethics of AI, it will be severely limited in its ability to do so if it is not leading the development and adoption of this technology. Europe would be wrong to forget that any competition involves winner and losers--and more often than not, the winners are those who compete with gusto.

Any organizations that are scaling up in size, locations, operations or products face exponential complexities. In this process of scaling up, data also grows in volume and variety, demanding innovation to more effectively derive value from quickly growing data. Data analytics is becoming table stakes as solutions have become more open and commoditized. Many organizations in the Asia Pacific region have adopted or experimented with emerging data solutions. Yet, according to a Data & Analytics Report by MIT and SAS in 2016, only 51% of respondents in 2015 believed analytics creates competitive advantages, down from 66% in 2012.