The irony of the ethical scandal enveloping Joichi Ito, the former director of the MIT Media Lab, is that he used to lead academic initiatives on ethics. After the revelation of his financial ties to Jeffrey Epstein, the financier charged with sex trafficking underage girls as young as 14, Ito resigned from multiple roles at MIT, a visiting professorship at Harvard Law School, and the boards of the John D. and Catherine T. MacArthur Foundation, the John S. and James L. Knight Foundation, and the New York Times Company. Many spectators are puzzled by Ito's influential role as an ethicist of artificial intelligence. Indeed, his initiatives were crucial in establishing the discourse of "ethical AI" that is now ubiquitous in academia and in the mainstream press. In 2016, then-President Barack Obama described him as an "expert" on AI and ethics. Since 2017, Ito financed many projects through the $27 million Ethics and Governance of AI Fund, an initiative anchored by the MIT Media Lab and the Berkman Klein Center for Internet and Society at Harvard University.

Most existing breast cancer screening programs are based on mammography at similar time intervals -- typically, annually or every two years -- for all women. This "one size fits all" approach is not optimized for cancer detection on an individual level and may hamper the effectiveness of screening programs. "Risk prediction is an important building block of an individually adapted screening policy," said study lead author Karin Dembrower, M.D., breast radiologist and Ph.D. candidate from the Karolinska Institute in Stockholm, Sweden. "Effective risk prediction can improve attendance and confidence in screening programs." High breast density, or a greater amount of glandular and connective tissue compared to fat, is considered a risk factor for cancer.

Artomatix, an Irish software company that has developed artificial intelligence (AI) technology, which can automate the creation of 3D content, has been acquired in a deal believed to be worth up to $60 million (€54 million). The buyer's name has not been disclosed but industry sources described it as a well-known Silicon Valley-based company that does not currently have a base in the Republic. The transaction, which closed late last week, is valued at between $50 million and $60 million, leading to a significant return for Artomatix's backers, which include Sure Valley Ventures and Enterprise Ireland. Sure Ventures, a London-listed investment firm founded by Irish entrepreneur Barry Downes which backs early-stage tech companies through its Sure Valley Ventures fund, said it expected to make about €1.6 million from the sale. This represents a fivefold return on its initial investment in Artomatix 14 months ago.

WITH record fines dished out over tech firms' use of personal data, and their public images becoming increasingly tarnished, this was the year the world started to turn against its tech giants. At the beginning of 2019, France's National Commission on Informatics and Liberty hit Google with a €50 million fine for lack of valid consent and transparency around personalised ads. In October, Facebook agreed to pay a fine of £500,000 to the UK Information Commissioner's Office for failing to protect users' personal information relating to the Cambridge Analytica scandal. Although the firm didn't admit fault over data misuse, this is the largest fine that could be issued. Amazon, Apple and Facebook all faced criticism this year over revelations that staff and contractors had listened to audio recordings of people speaking to virtual assistants Alexa and Siri, and voice chats recorded on Facebook Messenger.

In 2011, Apple unveiled its first iPhone with artificial intelligence, a personal assistant named Siri that could answer questions and help keep track of our daily lives. The AI revolution had begun, and it gave way to higher resolution cameras on phones, such as the then-new iPhone 4S, microphones and cameras in the home, everything from connected speakers, security devices, computers and even showers and sinks. By the end of the decade, we were carrying and or living with devices that are capable of tracking our every movement. Counties and states are selling our personal information to data brokers to resell it back to us, in the form of "people search engines." Facebook and Google have refined their tracking skills, in the pursuit of selling targeted advertising to marketers, that many people believe they are listening to us at all times. They are that good at serving up ads based on our interests, whether we want it or not.

Machine learning uses large volumes of data to make predictions about what will occur in the future, based on patterns extracted from past examples. However, a higher or lower degree of certainty always exists for each of these predictions, and this certainty can decrease when the data being used is especially complex. Machines' current ability to learn is present in many aspects of everyday life. Machine learning is behind the recommendations for movies we receive on digital platforms, virtual assistants' ability to recognize speech, or self-driving cars' ability to see the road. But its origin as a branch of artificial intelligence dates began several decades ago.

Note: MF Matrix factorization; BMF Bayesian matrix factorization; KBMF Kernel Bayesian matrix factorization; KRR Kernel ridge regression; NBR Network based regression; NBC Network based classification; CV Cross validation; LOOCV Leave-one-out cross validation; PCC Pearson correlation coefficient; RMSE Root mean square error; MSE Mean square error; SCC Spearman correlation coefficient; NDCG Normalized discounted cumulative gain; R2 Coefficient of determination; NRMSE Normalized root mean squared error; AUC Area under curve; PPI Protein–protein interaction.

Artificial intelligence brings lots of promises to the financial services industry, whether it's through automating processes or adding more convenience for their customers. But now we can quantify just how big of an enhancement AI will have on the bottom line for financial services companies around the globe. Accenture recently studied the changing face of the workforce as disruptive technologies become more prevalent in companies around the world. The consulting firm found 48% of tasks in the financial services industry could be augmented with technology by 2025, which will result in a big increase in productivity. AI, for example, could aid financial advisors in making real-time stock picks or help loan underwriters better gauge the risk of borrowers.

In our recent blog, we covered some exciting tech trends hitting 2020 such as autonomous driving, hyperautomation and more. There are many areas however with even more developments, ones you may have heard of and ones that you may have not. Technology is accelerating at such a rapid pace that every industry will be affected as well as the everyday consumer. We examine a further 5 top tech trends hitting our doors in 2020. At this stage, we all know or have at least heard of the cloud. With the likes of Amazon (AWS), Google and Microsoft competing with each other head to head, it's a hot industry with huge margins to be made.

Facebook's Artificial Intelligence (AI) Residency Program is a one-year research training position designed to give participants hands-on experience with artificial intelligence research while working in Facebook AI. The program will pair you with an AI Researcher and Engineer who will both guide your project. With the team, you will pick a research problem of mutual interest and then devise new deep learning techniques to solve it. We also encourage collaborations beyond the assigned mentors. The research will be communicated to the academic community by submitting papers to top academic venues as well as open-source code releases and/or product impact.