With both government and companies eagerly adopting artificial intelligence (AI) strategies, we explore how AI could also streamline and scale your business. We examine the potential opportunities and risks that come with using AI, and what the future of AI and business looks like. The CSIRO defines AI as "a collection of interrelated technologies used to solve problems autonomously and perform tasks to achieve defined objectives, in some cases without explicit guidance from a human being." Subfields of AI include machine learning, computer vision, human language technologies, robotics, knowledge representation and other scientific fields. For instance, AI is already being used in autonomous emergency breaking (helping reduce 1,137 vehicle-related deaths per year) and in maintaining Sydney Harbour Bridge (using machine-learning and predictive analytics to identify priority locations for maintenance).
The NSW bushfire inquiry final report has underscored a need to equip firefighters with more advanced technology, such as drones, remote sensors, data science, and artificial intelligence (AI), to help them better understand, model, and predict bushfire behaviour, and respond more quickly. "While noting that the 2019-20 fires were unlike anything seen in NSW before, the inquiry also notes that modern day technology and research advances have made us more capable of responding to them than at any time before," the report stated. "But we need to push our technological and our research capabilities much harder so that we can make massive improvements in fire and fire risk interpretation and response." The final report [PDF] is the result of an independent inquiry that examined the causes, preparation, and response to the state's devastating 2019-20 bushfires. A total of 76 recommendations were made and the state government have accepted them all.
The New South Wales government has announced it will be investigating how artificial intelligence, combined with data from satellites and local sensor networks, can be used to help speed up bushfire detection and predict fire behaviour. The research will be part of the 2020 Bushfire Data Quest, a week-long online sprint event that will see participation from universities, research institutes, philanthropy, and technology companies. NSW Deputy Premier and Minister responsible for Disaster Recovery John Barilaro said being able to help predict future bushfire activity will help prevent a repeat of Australia's catastrophic bushfire season last summer. "Predicting the behaviour of bushfires is a hugely difficult problem, made more complicated by a myriad of factors such as fuel load, atmospheric conditions, soil moisture, and availability of water," he said. "Using data from satellites is a great advancement on the tools we have traditionally used with much of the task of planning on-the-ground bushfire response relying on the experience and instincts of fire-fighters -- who are often volunteers. "We are investigating further how we use the data from multiple satellites and local sensor networks to create algorithms that will help detect fires earlier, predict fire behaviour, and help emergency services respond more effectively to protect homes, people and nature." The challenge is being carried out in partnership with the Minderoo Foundation wildlife and disaster resilience program, which aims to deliver a plan on how Australia and the rest of the world can prevent, mitigate, and defeat bushfires. The Minderoo Foundation program is currently being overseen by Adrian Turner, former CEO of the Commonwealth Scientific and Industrial Research Organisation's (CSIRO) Data61. He explained earlier this year how as part of developing a fire disaster strategy, new technologies would be piloted to help map where fires are likely to start and when they are most likely to occur, for instance. "We're looking at new satellite technology, we're looking at spatial intelligence infrastructure, we're looking at new classes of drones to be able to help with early detection," he said at the time. "Ultimately, we may get to a place where we have unmanned vehicles dropping new types of fire retardants.
Three friends were having morning tea on a farm in the Northern Rivers region in New South Wales (NSW), Australia, when they noticed a drilling rig setting up in a neighbor's property on the opposite side of the valley. They had never heard of the coal seam gas (CSG) industry, nor had they previously considered activism. That drilling rig, however, was enough to push them into action. The group soon became instrumental in establishing the anti-CSG movement, a movement whose activism resulted in the NSW government suspending gas exploration licenses in the area in 2014.2 By 2015, the government had bought back a petroleum exploration license covering 500,000 hectares across the region.3 Mining companies, like companies in many industries, have been struggling with the difference between having a legal license to operate and a moral4 one. The colloquial version of this is the distinction between what one could do and what one should do--just because something is technically possible and economically feasible doesn't mean that the people it affects will find it morally acceptable. Without the acceptance of the community, firms find themselves dealing with "never-ending demands" from "local troublemakers" hearing that "the company has done nothing for us"--all resulting in costs, financial and nonfinancial,5 that weigh projects down. A company can have the best intentions, investing in (what it thought were) all the right things, and still experience opposition from within the community. It may work to understand local mores and invest in the community's social infrastructure--improving access to health care and education, upgrading roads and electricity services, and fostering economic activity in the region resulting in bustling local businesses and a healthy employment market--to no avail. Without the community's acceptance, without a moral license, the mining companies in NSW found themselves struggling. This moral license is commonly called a social license, a phrase coined in the '90s, and represents the ongoing acceptance and approval of a mining development by a local community. Since then, it has become increasingly recognized within the mining industry that firms must work with local communities to obtain, and then maintain, a social license to operate (SLO).6 The concept of a social license to operate has developed over time and been adopted by a range of industries that affect the physical environment they operate in, such as logging or pulp and paper mills. What has any of this to do with artificial intelligence (AI)?
A teenager in New South Wales recently died after a fatal shark bite, adding to four other unprovoked shark-related deaths this year. These tragic events send shockwaves through the community and re-ignite our fear of sharks. They also fuel the debate around the best way to keep people safe in the water while minimising impacts on marine wildlife. This was the aim of a five-year trial of shark-mitigation technology--the Shark Management Strategy – which finished recently. The NSW government created this initiative in response to an unprecedented spike in shark bites in 2015, particularly on the north coast of NSW.
Earlier this year, the Australian Federal Police (AFP) admitted to using a facial recognition tool, despite not having an appropriate legislative framework in place, to help counter child exploitation. The tool was Clearview AI, a controversial New York-based startup that has scraped social media networks for people's photos and created one of the biggest facial recognition databases in the world. It provides facial recognition software, marketed primarily at law enforcement. The AFP previously said while it did not adopt the facial recognition platform Clearview AI as an enterprise product and had not entered into any formal procurement arrangements with the company, it did use a trial version. Documents published by the AFP under the Freedom of Information Act 1982 confirmed that the AFP-led Australian Centre to Counter Child Exploitation (ACCCE) registered for a free trial of the Clearview AI facial recognition tool and conducted a pilot of the system from 2 November 2019 to 22 January 2020.
We've got the roads, the rail and the airport to keep growing this nation, keep getting those products out of the warehouses and into people's shops and into people's homes," he said. Amazon's new hub is a "boost for this community," said NSW Premier Gladys Berejiklian. "People won't need to travel those longer distances to get the best jobs available. They'll be able to live and work near their communities, which is exactly what we want," Berejiklian said. Other retailers in Australia are gearing up for an increase in automation in their own logistics.
For better or worse, there's a good chance your current love life owes something to automation. Even if you're just hooking up with the occasional Tinder fling (which if you are, no judgment), you're still turning to Tinder's black-box algorithms to pick out that fling for you before turning to more black-box algorithms to pick out the best dingy bar to meet them at before turning to more black-box algorithms to figure out what, exactly, should be your date night lewk. If things get serious further down the line, you might turn to another black-box algorithm to plan your entire damn wedding for you. And if it turns out you got married for all the wrong reasons, it turns out there's another set of black boxes you can plug your details into to settle the details of your divorce. Known as "amica," the service was rolled out yesterday by the Australian government as a way to let soon-to-be-exes "make parenting arrangements" and "divide their money and property" without having to go through the hassle of hiring a lawyer to do the heavy lifting.
The Australian government has announced it will invest AU$19 million over three years into artificial intelligence-based health research projects designed to prevent, diagnose, and treat a range of health conditions. There are five projects in total that will receive funding as part of this announcement. The Centre for Eye Research Australia and the University of New South Wales (UNSW) will each receive nearly AU$5 million for their research projects. The Centre for Eye Research Australia has developed an AI system to detect eye and cardiovascular diseases, while UNSW is focused on using AI to understand and improve the treatment of mental health, including stress, anxiety, and depression. Another AU$7 million is being put towards two projects developed by the University of Sydney (USyd).
Knowledge Graphs (KGs) have gained considerable attention recently from both academia and industry. In fact, incorporating graph technology and the copious of various graph datasets have led the research community to build sophisticated graph analytics tools. Therefore, the application of KGs has extended to tackle a plethora of real-life problems in dissimilar domains. Despite the abundance of the currently proliferated generic KGs, there is a vital need to construct domain-specific KGs. Further, quality and credibility should be assimilated in the process of constructing and augmenting KGs, particularly those propagated from mixed-quality resources such as social media data. This paper presents a novel credibility domain-based KG Embedding framework. This framework involves capturing a fusion of data obtained from heterogeneous resources into a formal KG representation depicted by a domain ontology. The proposed approach makes use of various knowledge-based repositories to enrich the semantics of the textual contents, thereby facilitating the interoperability of information. The proposed framework also embodies a credibility module to ensure data quality and trustworthiness. The constructed KG is then embedded in a low-dimension semantically-continuous space using several embedding techniques. The utility of the constructed KG and its embeddings is demonstrated and substantiated on link prediction, clustering, and visualisation tasks.