If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
This may not be the best time to be thinking 15 years into the future, I know. For many associations, the rest of 2020 is stressful enough, and 2021 seems plenty forbidding too. But any association wise enough to have a strategic planning process knows that it has to look for potential headwinds. And a study released last week by the software company Citrix suggests that automation will have a substantial impact on leadership--calling to question what a leader might be good for, if AI can make decisions nearly as well as a human can. Citrix's report, Work 2035 [PDF], is based on the responses of 500 executives and 1,000 employees at large and mid-size companies in the United States and Europe, with a focus on artificial intelligence and productivity. In general, an always-on work mentality, combined with better analytics, have led people to wonder what role the C-suite ought to play.
"…In many organizations, the human resource department is responsible for many strategic tasks from managing the hiring to [the] termination of employee[s], for example monitoring of employees' at all the levels, handling payroll, managing employee[s'] benefits and so on. To make this work easier[,] organizations across the world are investing in HR automation [to] [carry] out the best human capital decision[s]…" I know what you're thinking: "…my company's board of directors is too visually impaired to consider what kind of impact these new-flanged capabilities will have on the company to actually consider them-- let alone implement them…" but you would be wrong to think this way; because the change is not only already happening, but it is accelerating. While it is true that some companies have not fully considered implementing a complete, top-to-bottom HR automation strategy -- largely because such a thing is still too abstract a problem and a not-so-clear-opportunity right now -- news like Amazon's drive to automate hiring and onboarding for its hourly warehouse workers will not stay secret for long. Do not kid yourselves, while corporate boards are not known for being bastions of innovation and forward-thinking, they know it's possible -- even if they are unable to see its affect on the corporation's current business -- at least, not yet, anyway.
The rapid advances of disruptive technologies such as artificial intelligence, automation, and others are transforming modern businesses. These technologies have paved ways for organizations to drive efficiency and become more productive. Most enterprises see AI and automation as a driving force of change that can lead to growth in their businesses. By leveraging them, companies, whether small, medium-sized or large, will maximize the return on investment of their marketing efforts. For instance, making use of an AI-powered chatbot that interacts directly with users can be a great entry point for business leaders to experience the power of AI.
The machine learning and AI-powered tools being deployed in response to COVID-19 arguably improve certain human activities and provide essential insights needed to make certain personal or professional decisions; however, they also highlight a few pervasive challenges faced by both machines and the humans that create them. Nevertheless, the progress seen in AI/machine learning leading up to and during the COVID-19 pandemic cannot be ignored. This global economic and public health crisis brings with it a unique opportunity for updates and innovation in modeling, so long as certain underlying principles are followed. Here are four industry truths (note: this is not an exhaustive list) my colleagues and I have found that matter in any design climate, but especially during a global pandemic climate. When a big group of people is collectively working on a problem, success may become more likely.
AI can impact and transform business IT operations. The technology has never been more useful as IT teams look to enable mass remote working during the Covid-19 pandemic. Nick McQuire, SVP, Enterprise Research at CCS Insight, explains that "the area of IT Helpdesk support has become a big use case for AI especially in the context of remote IT operations during the pandemic and we have seen the domain become a big focus for the likes of IBM recently with the launch of Watson AIOps, for example." Generally, he points out that AI can help business IT operations quickly diagnose problems and handle support tickets through greater automation. In some cases, "IT is also able to proactively fix problems based on predicting when an issue will arise," McQuire adds. Dr Iain Brown, head of data science at SAS UK & Ireland, says that it is "no understatement to say that AI can revolutionise business IT operations.
Some pairings create an exquisite experience that's simply not otherwise imaginable. The same is true of artificial intelligence (AI) and 5G networks. As all types of 5G-capable devices become more widely available, 5G networks roll out globally delivering greater than 10 times the speed at a fraction of the latency of 4G. Meanwhile, AI use cases for consumers and enterprises also continue to mature quickly. These two trends are significantly interrelated, and together have huge implications for consumers, enterprises and communication service providers (CSPs) alike.
The damage from pandemic-induced lockdowns, office and school closures and consumer retrenchment continue to reverberate through the economy. As the crisis drags into its seventh month, it has left businesses facing hard choices in adjusting to what now seems like many permanent changes. Required actions to address the COVID-19 crisis can be divided into three major stages: Respond, Recover and Thrive. These three stages are interspersed with two additional interim stages, and culminate in a long-term operating environment we call the'next normal'. The early months were focused on business survival through a series of reactionary changes, which was followed by mid-term operational stabilization in a world with diminished demand, continued socio-political restrictions and unpredictable events.
Artificial intelligence (AI) is no longer a thing of science fiction, it exists in the world all around us, automating simple tasks and dramatically improving our lives. But as AI and automation becomes increasingly capable, how will this alternative labor source affect your future workforce? In this article, we'll take a look at both some optimistic and pessimistic views of the future of our jobs amidst increasing AI capabilities. A two-year study from McKinsey Global Institute suggests that by 2030, intelligent agents and robots could replace as much as 30 percent of the world's current human labor. McKinsey suggests that, in terms of scale, the automation revolution could rival the move away from agricultural labor during the 1900s in the United States and Europe, and more recently, the explosion of the Chinese labor economy.
On the morning of November 9, 2016, the world woke up to the shocking outcome of the U.S. Presidential election: Donald Trump was the 45th President of the United States of America. An unexpected event that still has tremendous consequences all over the world. Today, we know that a minority of social bots--automated social media accounts mimicking humans--played a central role in spreading divisive messages and disinformation, possibly contributing to Trump's victory.16,19 In the aftermath of the 2016 U.S. elections, the world started to realize the gravity of widespread deception in social media. Following Trump's exploit, we witnessed to the emergence of a strident dissonance between the multitude of efforts for detecting and removing bots, and the increasing effects these malicious actors seem to have on our societies.27,29 This paradox opens a burning question: What strategies should we enforce in order to stop this social bot pandemic? In these times--during the run-up to the 2020 U.S. elections--the question appears as more crucial than ever. Particularly so, also in light of the recent reported tampering of the electoral debate by thousands of AI-powered accounts.a What struck social, political, and economic analysts after 2016--deception and automation--has been a matter of study for computer scientists since at least 2010. Via a longitudinal analysis, we discuss the main trends of research in the fight against bots, the major results that were achieved, and the factors that make this never-ending battle so challenging. Capitalizing on lessons learned from our extensive analysis, we suggest possible innovations that could give us the upper hand against deception and manipulation. Studying a decade of endeavors in social bot detection can also inform strategies for detecting and mitigating the effects of other--more recent--forms of online deception, such as strategic information operations and political trolls.
Automakers have already spent at least $16 billion developing self-driving technology, with the promise of someday creating fully autonomous vehicles.2 What has been the result? Although it seems that we have more promises than actual progress, some encouraging experiments are now under way, and there have been intermediate benefits in the form of driver-assist safety features. Engineers started on this quest to automate driving several decades ago, when passenger vehicles first began deploying cameras, radar, and limited software controls. In the 1990s, automakers introduced radar-based adaptive cruise control and dynamic traction control for braking.