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Where will homelessness rise or fall? A federally funded AI has some predictions

#artificialintelligence

Driving into York Region on Toronto's northern border, what first stands out to most people are the large houses and vast estates that Michael Braithwaite says leaves the impression that homelessness isn't an issue here. But it is - and Braithwaite says people in the sprawling region of nine municipalities are seeing the pressure points and trying to address them. "The region has a plan and they've got some good service providers like Blue Door and others in the community that are going to make it happen," said Braithwaite, the CEO of Blue Door shelters. "A lot has happened in the last 10 years, so I can't wait to see the next 10." Predicting the next decade is difficult, even more so in the next year or two given the impact of the pandemic on the country's economic and social services.


Challenges for Using Impact Regularizers to Avoid Negative Side Effects

arXiv.org Artificial Intelligence

Designing reward functions for reinforcement learning is difficult: besides specifying which behavior is rewarded for a task, the reward also has to discourage undesired outcomes. Misspecified reward functions can lead to unintended negative side effects, and overall unsafe behavior. To overcome this problem, recent work proposed to augment the specified reward function with an impact regularizer that discourages behavior that has a big impact on the environment. Although initial results with impact regularizers seem promising in mitigating some types of side effects, important challenges remain. In this paper, we examine the main current challenges of impact regularizers and relate them to fundamental design decisions. We discuss in detail which challenges recent approaches address and which remain unsolved. Finally, we explore promising directions to overcome the unsolved challenges in preventing negative side effects with impact regularizers.


Charles H. Turner, pioneer in animal cognition

Science

In the late 19th and early 20th centuries, Charles Henry Turner (1867–1923) established a research program that was in sharp contrast to prevailing ideas regarding animal behavior and cognition. Despite facing almost insurmountable barriers because of his African American ethnicity, he published more than 70 papers, including several in Science ([ 1 ][1]–[ 3 ][2]), on comparative brain anatomy in birds and invertebrates, individual variation of behavior and learning competences, and intelligent problem-solving in a large variety of animals, at a time when the dominant ideas only credited animals with the simplest of learning abilities. But his discoveries and conceptual advances failed to gain the recognition they deserved, and his works were later all but forgotten—indeed, some recent animal cognition research has reinvented wheels that had already been fashioned by Turner. Charles Darwin (1809–1882) and George Romanes (1848–1894) were famously generous in attributing intelligent behavior and mental abilities to animals, but their musings were largely based on observation and inference. The predominant experimentalist theories of animal behavior in the early 20th century, however, largely rejected notions of advanced animal intelligence or insight. Early ethologists such as Oskar Heinroth, Charles Whitman, and Wallace Craig focused instead on innate behavior and imprinting, a simple form of learning. Where problem-solving was observed, such as when animals open puzzle boxes, behaviorists such as Edward Thorndike proposed that this materialized as a result of trial and error, not insight or understanding of the nature of the challenge. None of these scientists were interested in individual variation of behavior. Enter Charles H. Turner, who took seriously Darwin's assertion of the importance of individual variation as well as the idea that humans were not the only intelligent animal species. But Turner backed up this possibility with a rigorous experimental approach. Turner was born just 2 years after the end of slavery in the United States in 1865. He obtained his M.Sc. from the University of Cincinnati in 1892 ([ 4 ][3]). In the same year, the 25-year-old published two single-author papers in Science —one of which was a short version of his B.Sc. work on the comparative anatomy of bird brains, whose relative size and complexity he compared with those of reptiles ([ 1 ][1]). Turner's verdict was, “When we compare the brain of a crow or a titmouse with the brain of a snake or a turtle, it is no longer a marvel that birds bear towards their reptilian cousins the relation of intellectual giants to intellectual dwarfs” [([ 1 ][1]), p. 16]. The same year also saw the publication of another remarkable study on variations in web building by gallery spiders ([ 5 ][4]) that contained key ingredients of Turner's distinct interpretation of animal behavior that was to accompany his entire body of work. Like many of his future papers, the study interfaces careful field observations with meticulously controlled laboratory work. Contrary to the still-popular view that spider web construction is a prime example of invertebrates' robotic, repetitive action patterns, Turner reported variation between individuals in adapting their construction to the geometry of available space and the functionality in capturing prey: “we may safely conclude that an instinctive impulse prompts gallery spiders to weave gallery webs, but the details of the construction are the products of intelligent action” [([ 5 ][4]), p. 110]. In the year of his Ph.D. (1907), Turner published on associative and spatial learning in ants and reported individual learning curves of their performance ([ 6 ][5]). Turner's focus on individual differences in behavior is a constant theme in his studies. It is deplorable that the now-popular field of “animal personality” has taken so little notice of Turner's trailblazing approach. The list of Turner's discoveries and insights that should have garnered attention, but did not, is long. Every student of animal behavior knows Nikolaas Tinbergen's study from 1932 on spatial learning, in which the later Nobel laureate (awarded for studies of individual and social behavior in animals) first marked a beewolf 's nest entrance with pine cones, then moved them to demonstrate that the insect was guided by a memory of the landmarks ([ 7 ][6]). But it is mostly unknown that Turner had already published similar findings in 1908, observing a solitary burrowing bee whose nest entrance was close to a discarded Coca Cola bottle cap. When the cap was moved to a nearby location next to an artificial burrow that Turner had made, the bee crawled into that burrow without hesitation—indicating, just as in Tinbergen's experiments, that the insect had a memory for landmarks rather than, for example, being guided by an instinct to follow the scent of the nest ([ 8 ][7]). In 1912, in a study that explored how a prey-carrying walking wasp finds its way home around obstacles in the path, Turner explicitly confronted Thorndike, affirming that the wasp's behavior is not explicable by trial-and-error learning and is instead consistent with a form of intentionality and an awareness of the desired outcome of the wasp's actions ([ 9 ][8]). Moreover, Turner found that an ant stuck on a small island began assembling a bridge to the “mainland,” using three different materials ([ 10 ][9]). The ant's behavior could not easily be explained by then-popular notions of instinct or trial-and-error learning; instead, the ant appeared to appreciate the nature of the problem, imagined a solution, and then worked toward this goal. The view that animals are capable of insightful problem-solving was also apparent in Turner's interpretation of his field observations of the hunting behavior of a snake pursuing a lizard ([ 3 ][2]). The lizard had escaped up a tree and looked downward where it expected the snake to launch the next attack. The snake, which had been pursuing the lizard for some time, instead ascended another tree, crossed over when it had reached a point higher than the lizard, and then attacked from behind. These observations are reminiscent of the detour behavior seen when jumping spiders hunt—discovered in the 1990s ([ 11 ][10]). It is remarkable that Turner's views on animal intentionality preceded present-day explorations of the same topic by a century. Even though his experimental work was known to contemporary giants such as John Watson and Thorndike ([ 4 ][3]) and across the Atlantic by later Nobel laureate Karl von Frisch, Turner's visionary ideas about animal intelligence did not resonate in the field; perhaps they were simply too far ahead of the time. Accordingly, they are almost completely unrecognized in the current literature. Further highlighting the importance and insightful nature of Turner's work, in 1913 he reported on the effects of age and sex on cockroaches trained to navigate mazes ([ 12 ][11]). Turner found that individuals placed an emphasis on either speed or accuracy: Older cockroaches choose slowly but more precisely. Extraordinarily, Turner suggests that the hesitation that cockroaches display when evaluating their options bears the hallmarks of will, a facet of consciousness. The question of whether humans and other animals exhibit free will continues to generate controversy among neuroscientists and philosophers. That insights from insect behavior could contribute to this debate has only recently been suggested again by neuroscientist Martin Heisenberg ([ 13 ][12]), who proposed that insects display an awareness of the consequences of their actions and evidence of free will in deciding between options. ![Figure][13] From Charles H. Turner to comparative cognition: 1850–2020 Charles H. Turner made important observations about animal cognition, which went against the leading paradigms of the time. His ideas have stood the test of history, but Turner's work has largely been forgotten, likely because his ethnicity prevented him from becoming a research team leader and so he could not train scientists who might have continued his approach. Turner was active in the U.S. civil rights movement and advocated that education is key to overcoming ethnic barriers in society. GRAPHIC: V. ALTOUNIAN/ SCIENCE ; (IMAGES, CLOCKWISE FROM LEFT) WIKIMEDIA COMMONS;C. H. TURNER ET AL. ([ 12 ][11]); ST. LOUIS GLOBE-DEMOCRAT , 3 JULY 1917, P. 1 Why is Turner not more widely credited as a major luminary in research on animal intelligence? Turner faced substantial obstacles because of his ethnicity. Despite publishing many important papers, he was not given a post at a major U.S. research university. Turner's work was thus conducted without access to state-of-the-art laboratory facilities or library resources. One reason for Turner's relative obscurity today may be that he had no possibility of mentoring research students who would have carried his ideas into subsequent generations. For comparison, Russian Nobel laureate Ivan Pavlov (1849–1936), famed for his studies on classical conditioning, trained more than 140 co-workers. One cannot help but wonder what Turner might have achieved if he had had comparable resources and manpower. The entire field of animal cognition may have developed differently. Would a “cognitive revolution” have been needed against the dominant ideas of behaviorism that ruled psychology for the first half of the 20th century (postulating that learning largely happens in the form of simple associations), if Turner's ideas about advanced cognition in animals had generated a movement at the time he expressed them? African American historian William Du Bois (1868–1963) lamented that “C. H. Turner, one of the great world authorities on insects, nearly entered the faculty of Chicago University; but the head professor who called him died, and his successor would not have a “N\---|--,” despite a reputation which was European; Turner died in a high school of neglect and overwork” [([ 4 ][3]), p. 348]. The institution at which Turner taught from 1908 to 1922 was Sumner High School, a school for African American children in St. Louis. During his time there, he and his pupils would have witnessed the East St. Louis massacre in 1917, during which white mobs murdered more than 100 African Americans; another 6000 lost their homes as a result of arson attacks on their neighborhoods ([ 14 ][14]). Turner was active in the U.S. civil rights movement, and years before coming to St. Louis, he wrote that an emphasis on high-quality education and a conscious effort to abandon prejudices might eliminate barriers between Blacks and whites within a few decades ([ 15 ][15]). One would hope that nowadays, a person of Turner's caliber might not face similar adversity in terms of academic employment opportunities or long-term recognition of their contribution to science. But even today, very few scholars in animal cognition, or indeed across biology, are Black. Turner clearly recognized the importance of ethnic-minority role models from the earliest stages of education; their near-complete absence in a field of scholarly study will require concerted counterefforts. Funded summer schools for ethnic minority students can also make a substantial difference to inspire budding scientists. Institutions must make still-stronger efforts to eliminate biases in hiring, promotions, and salary decisions and to celebrate the successes of ethnic minority scholars. Even where they do (and there is likely plenty of room for improvement), overt or poorly concealed racism is still commonly experienced by underrepresented ethnic groups, even in academia. This will likely discourage many aspiring scientists from venturing further. A hopeful development is that some conference organizers are taking steps in the right direction to increase inclusivity; for example, the Animal Behavior Society annually supplies the Charles H. Turner award that prioritizes traditionally underrepresented groups for conference travel funding. More than ever, humanity needs to be inclusive to confront current and future challenges. Diversity increases the pool of talent and, as Turner's example shows, has the potential to transform entire fields. 1. [↵][16]1. C. H. Turner , Science 19, 16 (1892). [OpenUrl][17][CrossRef][18][PubMed][19] 2. 1. C. H. Turner , Science 20, 39 (1892). [OpenUrl][20] 3. [↵][21]1. C. H. Turner , Science 30, 563 (1909). [OpenUrl][22][FREE Full Text][23] 4. [↵][24]1. C. I. Abramson , Annu. Rev. Entomol. 54, 343 (2009). [OpenUrl][25][CrossRef][26][PubMed][27] 5. [↵][28]1. C. H. Turner , J. Comp. Neurol. 2, 95 (1892). [OpenUrl][29] 6. [↵][30]1. C. H. Turner , J. Comp. Neurol. Psychol. 17, 367 (1907). [OpenUrl][31] 7. [↵][32]1. N. Tinbergen , J. Comp. Physiol. A Neuroethol. Sens. Neural Behav. Physiol. 16, 305 (1932). [OpenUrl][33] 8. [↵][34]1. C. H. Turner , Biol. Bull. 15, 247 (1908). [OpenUrl][35] 9. [↵][36]1. C. H. Turner , Psyche 19, 100 (1912). [OpenUrl][37] 10. [↵][38]1. C. H. Turner , Biol. Bull. 13, 333 (1907). [OpenUrl][39][CrossRef][40] 11. [↵][41]1. M. S. Tarsitano, 2. R. R. Jackson , Behaviour 131, 65 (1994). [OpenUrl][42][CrossRef][43] 12. [↵][44]1. C. H. Turner , Biol. Bull. 25, 348 (1913). [OpenUrl][45] 13. [↵][46]1. M. Heisenberg , Nature 459, 164 (2009). [OpenUrl][47][CrossRef][48][PubMed][49][Web of Science][50] 14. [↵][51]1. J. N. Harrington , Buzzing with Questions: The Inquisitive Mind of Charles Henry Turner (Boyds Mills Press, 2019). 15. [↵][52]1. C. H. Turner , in Twentieth Century Negro Literature (J. L. Nichols, 1902), pp. 162–166. 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Danger! You're Using The Wrong Data To Teach AI!

#artificialintelligence

Data is the fuel for artificial intelligence. The more data we have, the better the AI will learn and find those hidden patterns, right? We have the ability to collect LOTS of data. Consider the nearly 31 billion IoT devices producing information for machine consumption. However, lots of data does not translate into good data.


Will the technological singularity change everything we know about AI? - Create

#artificialintelligence

The idea of a technological singularity -- a point where advancement passes a certain point and runs away from us -- gets traced back to computer scientist and polymath John von Neumann in the 1950s. In recent years, that date at which artificial intelligence outstrips human intelligence has become a question asked of computer scientists, engineers and others who might be better placed than the layperson to speculate. Putting aside issues such as the difficulty in defining and measuring "intelligence", here are some educated guesses. According to Rodney Brooks, the iRobot and Robust.AI co-founder, the date for human-level AI might be 2300. A median prediction based on a survey of 300 colleagues by University of NSW Professor of Artificial Intelligence Toby Walsh foresaw the year 2062.


AI Taking A Knee: Action To Improve Equal Treatment Under The Law

#artificialintelligence

In the wake of the George Floyd tragedy and so many other appalling cases like it, there is a growing question if a solution lies with robot police powered by artificial intelligence (AI.) In theory, AI cops could reduce biased and discriminatory practices and improve access to justice. Pop culture is filled with heroes like this such as Robocop and CHAPPiE. However, reality maybe a little stranger than fiction in this case as there are already some robots already in action for law enforcement. Let's start with Robo-Guard, which works in the South Korean prison system.


CSIRO names Jon Whittle as Data61's new boss

ZDNet

The Commonwealth Scientific and Industrial Research Organisation (CSIRO) has appointed Jon Whittle as the director of Data61. Whittle, who will start his new role in July, is set to join from Monash University where he is currently executive dean of the Faculty of Information Technology and founding co-director of the Monash Data Futures Institute. Whittle was previously a senior research scientist and technology area lead at NASA Ames Research Center where he led artificial intelligence-related research and development projects in civil engineering and space technologies. "Since we created Data61 as part of Strategy 2020, CSIRO has become home to Australia's leading data science and innovation group, partnering with government, industry and academia to solve Australia's largest data-driven challenges underpinned by deep science and technology," CSIRO chief executive Larry Marshall said. "Jon is well placed to take CSIRO's digital journey into its next phase, maximising the opportunities that digital and data science can deliver for the nation, and the world."


New AI System Translates Human Brain Signals Into Text With Up to 97% Accuracy

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The world is only just getting used to the power and sophistication of virtual assistants made by companies like Amazon and Google, which can decode our spoken speech with eerie precision compared to what the technology was capable of only a few short years ago. In truth, however, a far more impressive and mind-boggling milestone may be just around the corner, making speech recognition seem almost like child's play: artificial intelligence (AI) systems that can translate our brain activity into fully formed text, without hearing a single word uttered. Brain-machine interfaces have evolved in leaps and bounds over recent decades, proceeding from animal models to human participants, and are, in fact, already attempting this very kind of thing. Just not with much accuracy yet, researchers from the University of California San Francisco explain in a new study. To see if they could improve upon that, a team led by neurosurgeon Edward Chang of UCSF's Chang Lab used a new method to decode the electrocorticogram: the record of electrical impulses that occur during cortical activity, picked up by electrodes implanted in the brain.


How artificial intelligence will save teachers time

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Teachers spend about 20% to 40% of their time--or about 13 hours a week--on activities that could be automated using technology, according to a new report on artificial intelligence by the management consulting firm McKinsey & Company. Preparation time has the biggest potential for automation, making teachers more effective and efficient in lesson planning. For instance, adaptive math software lets teachers more quickly and accurately assess student performance, place learners in groups and provide the next assignments. Collaboration platforms, meanwhile, allow teachers to share relevant materials. "Technology has the least potential to save teacher time in areas where teachers are directly engaging with students: direct instruction and engagement, coaching and advisement, and behavioral-, social-, and emotional-skill development," the report found.


Why KPMG is treating employees who want to learn AI to a $450 million training center that feels like a luxury resort

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Promoting the company's culture was a top priority when KPMG was making preliminary plans for its new $450 million training facility. It emerges in different ways throughout the 800,000-square-foot facility, some more subtle than others. The hallway to the main conference space, for example, is lined with artifacts from KPMG's heritage, including a ledger from original founder James Marwick dating to 1898. In another area, a set of lights that hang over the cafeteria change colors -- a nod to the importance of diversity at the firm. "There are things that the physical representation here is designed to really reflect what we see as our core kind of cultural aspects," said chief financial officer David Turner.