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Fake Accounts On Social Media Now Able To Copy Human Behaviour

Fake accounts enabled by Artificial Intelligence (AI) on social media have evolved and are now able to copy human behaviour

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fake, media, behaviour, artificial intelligence
Social Media Icons. VOA

Researchers, including one of Indian-origin, have found that bots or fake accounts enabled by Artificial Intelligence (AI) on social media have evolved and are now able to copy human behaviour to avoid detection.

For the study published in the journal First Monday, the research team from the University of Southern California examines bot behaviour during the 2018 US presidential elections compared to bot behaviour during the 2016 US elections.

“Our study further corroborates this idea that there is an arms race between bots and detection algorithms. As social media companies put more efforts to mitigate abuse and stifle automated accounts, bots evolve to mimic human strategies. Advancements in AI enable bots producing more human-like content,” said study lead author Emilio Ferrara.

fake, media, behaviour, artificial intelligence
Artificial Intelligence (AI) on social media have evolved and are now able to copy human behaviour to avoid detection. Pixabay

The researchers studied almost 250,000 social media active users who discussed the US elections both in 2016 and 2018 and detected over 30,000 bots.

They found that bots in 2016 were primarily focused on retweets and high volumes of tweets around the same message.

However, as human social activity online has evolved, so have bots. In the 2018 election season, just as humans were less likely to retweet as much as they did in 2016, bots were less likely to share the same messages in high volume.

Bots, the researchers discovered, were more likely to employ a multi-bot approach as if to mimic authentic human engagement around an idea.

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Also, during the 2018 elections, as humans were much more likely to try to engage through replies, bots tried to establish the voice and add to the dialogue and engage through the use of polls, a strategy typical of reputable news agencies and pollsters, possibly aiming at lending legitimacy to these accounts.

In one example, a bot account posted an online Twitter poll asking if federal elections should require voters to show ID at the polls. It then asked Twitter users to vote and retweet.

“We need to devote more efforts to understand how bots evolve and how more sophisticated ones can be detected. With the upcoming 2020 US elections, the integrity of social media discourse is of paramount importance to allow a democratic process free of external influences,” Ferrara said. (IANS)

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Is Oracle Digital Assistant Smarter Than Amazon Alexa? Find It Out Here

Here's Why Oracle's digital assistant better than Amazon's Alexa

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Amazon Alexa may lag behind Oracel Digital Assistant. Pixabay

Alexa may be your perfect living room assistant, but when it comes to specific queries with particular vocabulary from enterprises, it lags behind in rich capabilities that Oracle Digital Assistant (ODA) has to offer, a top company executive has stressed.

Oracle Digital Assistant can become your intelligent front-end — your smart router that’s able to send all your specific questions to relevant bots, according to Suhas Uliyar, VP-Product Management, Oracle Digital Assistant and Integration Cloud.

“It knows how to handle conflicts, manage security and so on and so forth. It has got Artificial Intelligence (AI) and is AI-trained so we call the routing of your questions to be relevant, and call it a skill now. Instead of bot, it’s a skill,” Uliyar told IANS during an interaction.

According to him, there are a couple of differences compared to Alexa as it works on the same model.

“Alexa is very implicit, where you have to say — Alexa, ask this skill to do something. While Oracle Digital Assistant is both explicit and implicit and you don’t need to sort of say ‘go ask the HCM (Human Capital Management) bot,’ for instance. It’ll just figure out that the question is for HCM bot and will answer accordingly,” Uliyar elaborated.

The other thing is to use the word ‘assistant’ and, according to him, we are overloading the term ‘assistant’ because if you have an ‘assistant’, she or he is smart enough to understand who you are, what your preferences are, know how you work.

“Most of the chatbots respond to a simple question and answer. Next time, it will probably remember who you are. So, the whole context is memory, and also the process side of things,” the Oracle executive added.

Oracle Digital Assistant provides the platform and tools to easily build AI-powered assistants that connect to your backend applications.

The digital assistant uses AI for natural language processing and understanding, to automate engagements with conversational interfaces that respond instantly, improve user satisfaction, and increase business efficiencies.

Most of those voice-enabled application programming interfaces (APIs) are being trained using what’s called Open Common Domain Models, which means that it understands our normal speaking style and content.

“What if an enterprise has a specific vocabulary? For example, a very common thing in Enterprise Resource Planning (ERP) is what’s EBITDA for a company. You try saying EBITDA to Alexa or any other such assistant in the market today, and you’ll most likely draw a blank,” Uliyar told IANS.

Oracle AI
Oracle digital assistant uses AI for natural language processing and understanding. Pixabay

Earnings before interest, tax, depreciation and amortization (EBITDA) is a measure of a company’s operating performance.

According to him, to serve customers with delightful experiences every single time, there has to be a lot of innovation happening — whether it’s mobile, chatbots, Blockchain, AI or AR/VR.

“With all these new realities, what enterprises really need is a platform that can pull that ‘holistic experience’ altogether. That’s sort of the topmost challenge that enterprise customers want to solve,” he noted.

Oracle Digital Assistant is very sophisticated. It has got deep learning and is based on a technology called Sequence-to-Sequence vectoring and creates what we call as logical forms of the statement.

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“We call it a deep semantic parsing. It’s the underlying technology and is very different given the advancements of deep learning. We can do a much better job instead of understanding the linguistic constructs, versus in the past. This is quite a bit of advancement. We’re definitely very excited about pushing the boundaries,” said Uliyar. (IANS)