We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. While it's true that the adoption of artificial intelligence in various applications is yielding tangible results for all kinds of enterprises, there is a downside: AI's full potential isn't being realized because of a lack of human expertise to optimize it for business purposes. A new global research project conducted by Juniper Networks and Wakefield Research and released June 15 shows an increase in AI adoption during the last 12 months, but a shortage of human talent is holding a great deal of good implementation back. Governance policies involving AI continue to lack maturity, the report said, and this is also a stumbling block. Both of these factors are needed to responsibly manage AI's growth when considering privacy issues, regulation compliance, hacking and AI terrorism, the survey said.
We're sure you've heard the claim that "data is the new oil". Web scraping is the process of mining data from the World Wide Web for a specific purpose. In the most simple form, it is copying and pasting a specific set of information to a local database for archival use, scientific analysis, or some other use. Some of the most widely used examples include aggregator websites which provide price comparisons for online goods. There are also sites like archive.orgthat
Shamed and appalled by the brutal murder of Sarah Everard at the hands of a serving officer, the British public demanded a swift response from the Metropolitan Police Service. A subsequent review into the conduct of officers based at Charing Cross in London unearthed a toxic environment where colleagues bonded over jokes about rape, killing black children and beating their wives. Heads had to roll, starting with the former Met Police Service commissioner Dame Cressida Dick. The poor handling of the Everard case did little to assuage conclusions by its own watchdog that the Met is "systematically and institutionally corrupt". Inspector of Constabulary Matt Parr said that the Met had "sometimes behaved in ways that make it appear arrogant, secretive and lethargic" in response to investigations into dirty cops, and that it did "not have the capability to proactively monitor" communications with any effect, "despite repeated warnings from the inspectorate".
The Artificial Intelligence Act was introduced to the European Union in April 2021, and is rapidly progressing through comment periods and rewrites. When it goes into effect, which experts say could occur at the beginning of 2023, it will have a broad impact on the use of AI and machine learning for citizens and companies around the world. The AI law aims to create a common regulatory and legal framework for the use of AI, including how it's developed, what companies can use it for, and the legal consequences of failing to adhere to the requirements. The law will likely require companies to receive approval before adopting AI for some use cases, outlaw certain other AI uses deemed too risky, and create a public list of other high-risk AI uses. At a broad level, the law seeks to codify the EU's trustworthy AI paradigm, according to an official presentation on the law by the European Commission, the continent's governing body.
It is well-established that accounting is a data-intensive stream. It is filled with numerical, non-numerical, statistical and non-statistical data. There is data involved in invoices, purchase orders, employee salaries, daily expenses and a load of other things. Such enormous amounts of data can get overwhelming after a point. Accounting professionals have to undergo a tedious process to collect and analyze such enormous amounts of data. Moreover, the data is scattered at various sources.
According to the Global Economic Crime and Fraud Report conducted by the global audit firm PwC, financial fraud and cybercrime hit an all-time high this year. In fact, in the past two years, 49% of international organizations reported experiencing economic fraud. While numerous institutions are introducing new technologies to eradicate crime, technology to prevent economic crime and fraud with artificial intelligence is attracting attention. According to a report by PwC, there are three common types of economic crime and fraud. These are asset theft, cybercrime, and consumer fraud.
The sheer potential of facial recognition technology in various fields is almost unimaginable. However, certain errors that commonly creep into its functionality and a few ethical considerations need to be addressed before its most elaborate applications can be realized. An accurate facial recognition system uses biometrics to map facial features from a photograph or video. It compares the information with a database of known faces to find a match. Facial recognition can help verify a person's identity, but it also raises privacy issues. A few decades back, we could not have predicted that facial recognition would go on to become a near-indispensable part of our lives in the future.
Artificial Intelligence (AI) Patent Application filings continue their explosive growth trend at the U.S. Patent Office (USPTO). At the end of 2020, the USPTO published a report finding an exponential increase in the number of patent application filings from 2002 to 2018. In addition, current data shows that AI-related application filings pertaining to graphics and imaging are taking the lead over AI modeling and simulation applications. In the last quarter of 2020, the United States Patent and Trademark Office (USPTO) reported that patent filings for Artificial Intelligence (AI) related inventions more than doubled from 2002 to 2018. See Office of the Chief Economist, Inventing AI: Tracking The Diffusion Of Artificial Intelligence With Patents, IP DATA HIGHLIGHTS No. 5 (Oct.
On April 21, the EU officially proposed the Artificial Intelligence Act, outlining the ability to monitor, regulate and ban uses of machine learning technology. The goal, according to officials, is to invest in and accelerate the use of AI in the EU, bolstering the economy while also ensuring consistency, addressing global challenges and establishing trust with human users. AI use cases with unacceptable risk will be banned outright. High-risk applications, similarly, pose a high risk to health, safety and fundamental rights, though the debate around the definition of "high risk" has been raging since last year, with more than 300 organizations weighing in. These AI applications are allowed on the market only if certain safeguards are in place, such as human oversight, transparency and traceability.
Developments in the field of artificial intelligence (AI) are moving quickly. The EU is working hard to establish rules around AI and to determine which systems are welcome and which are not. But how does the EU do this when the biggest players, the US and China, often have different ethical views? Political economist Daniel Mügge and his team will conduct research into how the EU conducts its'AI diplomacy' and will sketch potential future scenarios. "Our research is essentially about regulation around AI", says political economist Daniel Mügge.