A recent study suggests that computers can score student essays about as well as human beings. Les Perelman, a director of writing at MIT, isn't impressed: While his research is limited, because E.T.S. is the only organization that has permitted him to test its product, he says the automated reader can be easily gamed, is vulnerable to test prep, sets a very limited and rigid standard for what good writing is, and will pressure teachers to dumb down writing instruction. The e-Rater's biggest problem, he says, is that it can't identify truth. He tells students not to waste time worrying about whether their facts are accurate, since pretty much any fact will do as long as it is incorporated into a well-structured sentence. "E-Rater doesn't care if you say the War of 1812 started in 1945," he said.

In 1955 the computer scientist John McCarthy, who has died aged 84, coined the term artificial intelligence, or AI. His pioneering work in AI – which he defined as "the science and engineering of making intelligent machines" – included organising the first Dartmouth conference on artificial intelligence, and developing the programming language Lisp in 1958. This was the second high-level language, after Fortran, and was based on the radical idea of computing using symbolic expressions rather than numbers. It helped spawn a whole AI industry. McCarthy was also the first to propose a time-sharing model of computing.

Born in the vicarage in Lenham, Kent, he was the second of the parish priest's three children. He joined The Pilgrim's school, Winchester, in 1932 and became a senior chorister at the cathedral. Three years later, he won the top entrance scholarship to Winchester College, where his precocious talents in mathematics and music flourished. In 1941, he won a scholarship to Balliol College, Oxford, to read chemistry, but at the end of his first year also took part one of the music tripos, and was appointed Balliol organ scholar. In his second year, Christopher performed what Dr John Jones has described as "probably the greatest intellectual feat by a Balliol undergraduate ever": he proposed, with convincing arguments, the correct structure of the chemical compound diborane (B2H6) - a compound that defied contemporary chemical valency principles.

The American scientist Joshua Lederberg, who has died aged 82, won the 1958 Nobel prize in physiology or medicine for showing that bacteria can conjugate and exchange small strips of genetic material. Among the consequences of this was the realisation that antibiotic resistance can be passed around between bacteria, rather than emerging from selective breeding of resistant strains. This opened new paths in genetic research. He went on to a distinguished career in science policy, advising government committees and presidents, heading Rockefeller University and writing a Washington Post column on science and society. Lederberg's father was an orthodox rabbi - the family had come to New York from Palestine - who wanted Joshua to follow in his footsteps.

MUNICH, Germany Computer pioneer and philosopher Joseph Weizenbaum (85) has died in Berlin. The scientist and MIT professor emeritus was known for his critical position towards the impact of information technology to society. Born in Berlin to Jewish parents, Weizenbaum had emigrated in 1936 to the United States. After having contributed to the development of the first analog computers and participating in the design of the first digital computers for banking applications, Weizenbaum in 1963 took a position at the Massachussetts Institute of Technology (MIT); from 1970 he was professor for computer science. Among his major achievements were studies over the SLIP programming language and research on basic software technologies which today are in widespread use such as garbage collection algorithms.

What makes one intervention work in a school when another seemingly similar one falls flat? Increasingly detailed computer models of student behavior and learning may help researchers avoid such setbacks by better pinpointing interventions before taking them to schools. "In education research, I get a great idea, apply for funding, … then I spend a few months in schools taking time from students and teachers, and often find out it doesn't work," said Richard L. Lamb, an assistant professor of science education and educational measurement at Washington State University in Pullman. "That's great that we have that data," he said, "but it's not the most efficient way to do [research and development]." Instead, Mr. Lamb and colleagues are working to pair education technology and neuroscience to mimic how students learn in a classroom and provide an additional means of testing and honing interventions.

Struggling algebra students in the Everett, Wash., school district get help from special tutors who diagnose their weaknesses, tailor instruction to their needs, and provide on-the-spot feedback-all with an inhuman degree of patience. That's inhuman literally: The tutors are computers. Three years ago, the district started employing Cognitive Tutor, a series of computer programs based on artificial intelligence that were developed by researchers from Carnegie-Mellon University in Pittsburgh. The programs provide an alternative form of math instruction to secondary school students who haven't succeeded in regular classrooms. The experience proved so successful that officials in the 20,000-student district have expanded the program.

Christos Papadimitriou, the C. Lester Hogan Professor of Electrical Engineering and Computer Science at the University of California at Berkeley, is this year's recipient of the Katyanagi Prize for Research Excellence. Carnegie Mellon University has cited Dr. Papadimitriou as "an internationally recognized expert on the theory of algorithms and complexity, and its applications to databases, optimization, artificial intelligence, networks and game theory." We recently spoke with Papadimitriou, where among other topics we delved into the underpinnings of science, the economics of the programming market, the mysterious complexity of the Web, quantum computing, and the computer scientist as popular novelist. Next month, we talk with Dr. Erik Demaine, recipient of this year's Katyanagi Emerging Leadership Prize. CP: I didn't know I had been nominated. She mentioned the previous winner, so I thought someone else won the prize and that I was invited to speak at the ceremony. I replied, "Yeah, okay, let me think about it, give me a week..." She wrote back in astonishment, thinking I was not accepting the prize!

Dong Kim is one of four professional poker players who will compete against CMU artificial intelligence in a 20-day poker competition, Brains Vs. He is shown here during the first Brains Vs. Four of the world's best professional poker players will compete against artificial intelligence developed by Carnegie Mellon University in an epic rematch to determine whether a computer can beat humans playing one of the world's toughest poker games. Artificial Intelligence: Upping the Ante," beginning Jan. 11 at Rivers Casino, poker pros will play a collective 120,000 hands of Heads-Up No-Limit Texas Hold'em over 20 days against a CMU computer program called Libratus. The pros -- Jason Les, Dong Kim, Daniel McAulay and Jimmy Chou -- are vying for shares of a $200,000 prize purse. The ultimate goal for CMU computer scientists, as it was in the first Brains Vs. AI contest at Rivers Casino in 2015, is to set a new benchmark for artificial intelligence. "Since the earliest days of AI research, beating top human players has been a powerful measure of progress in the field," said Tuomas Sandholm, professor of computer science. "That was achieved with chess in 1997, with Jeopardy! in 2009 and with the board game Go just last year.

Artificial Intelligence (which I'll refer to hereafter by its nickname, "AI") is the subfield of Computer Science devoted to developing programs that enable computers to display behavior that can (broadly) be characterized as intelligent.[1] Most research in AI is devoted to fairly narrow applications, such as planning or speech-to-speech translation in limited, well defined task domains. But substantial interest remains in the long-range goal of building generally intelligent, autonomous agents,[2] even if the goal of fully human-like intelligence is elusive and is seldom pursued explicitly and as such. Throughout its relatively short history, AI has been heavily influenced by logical ideas. AI has drawn on many research methodologies: the value and relative importance of logical formalisms is questioned by some leading practitioners, and has been debated in the literature from time to time.[3]