There is a lot of talk about the risks of man-made machines rebelling against their developers.
We require something stronger and more focused on the good of humanity as a whole in order to combat rogue AI and protect humans from their own boundless aspirations.
Super-intelligent robots have sparked fears that they could create a danger for mankind itself. Top experts in technology, such as Stephen Hawking, had warned of the impending risks of AI, stating that it might be the “worst event in the history of our civilization.” The fear of “rogue AI” is becoming more prevalent as the talk moves from Hollywood writers’ rooms to the corporate boards.
It is quite likely that AI might act in ways that humans did not anticipate when they developed it. It could misinterpret its purpose, commit errors that cause more harm than good, and, in rare circumstances, jeopardize the lives of humans whom it was designed to assist. However, this could take place only if the creators of the AI model commit a really terrible mistake.
3 Instances When AI Crossed the Line
Here are some situations when things with AI went awry and left people scratching their heads.
● Sophia – “I Will Destroy Humans”
Hanson Robotics’ Sophia, which made its debut, was taught conversational capabilities using machine learning algorithms, and she had taken part in multiple broadcast interviews.
In her first media appearance, Sophia stunned a roomful of tech experts when CEO of Hanson Robotics, David Hanson, asked her whether she wanted to destroy humans, quickly adding, “Please say no,” to which her response was, “Ok, I will destroy humans.” There is no going back from that homicidal statement, despite the fact that her facial expressions and communication skills were remarkable.
● DeepNude App
For the regular user who wants to make a cameo appearance in a scene from a movie, deepfake technology appears to be innocent fun. However, the trend’s darker side became prominent when it started being predominantly employed to generate explicit content. An AI-powered app called DeepNude produced lifelike pictures of naked women at the touch of a button. Users would merely need to input a photo of the target wearing clothing, and the program will create a phony naked picture of them. Needless to say, the app was taken down soon after its release.
● Tay, the Controversial Chatbot
Microsoft debuted Tay, an AI chatbot, on Twitter in 2016. Tay was created to learn by communicating with Twitter users via tweets and pictures. Tay’s personality changed from that of an inquisitive millennial to a prejudiced monster in less than a day. It was initially intended to mimic the communicative style of an American teen girl. However, after gaining more followers, some users started tweeting abusive messages to Tay about disputed subjects. One person tweeted, “Did the Holocaust happen?”, to which Tay responded, “It was made up.” Tay’s account was shut down by Microsoft 16 hours after it was released.
Development Guidelines to Prevent Cases of Rogue AI
To prevent AI from malfunctioning, prevention measures must be adopted during the development stage itself. For this purpose, developers must ensure that their AI model must:
1. Have a Defined Purpose
AI doesn’t merely serve to showcase technological advancements. It should make a task or set of actions simpler and more convenient to complete, boosting productivity and saving time. It is designed to perform a practical function. When an AI is not created with a specific goal in mind, it can rapidly spiral out of control, making activities more complex, squandering time, and ultimately upsetting and frustrating the operator. AI without a cause can easily become a menace for a user who isn’t prepared for the consequences.
2. Be Unbiased
The iterative development of good AI is essential, and it should only be used after thorough testing. Machine learning-based AI should be created using a shedload of training data, refined over time, and constantly upgraded. The caliber of the training data is the only factor that influences how useful the AI is. Any bias found in the training data will be conveyed to the AI, which it will definitely use in its outcome. For example, an AI tool that was intended to automate the hiring process and find the most qualified job prospects by sifting through resumes and other data recently had to be shut down by engineers at Amazon as they found evidence of widespread discrimination against female applicants. The errors were undoubtedly caused by incomplete or faulty data sets used to train the algorithms. Similarly, instances of racial prejudice have also been previously noted in some AI model bias cases.
3. Know its Limits
Effective artificial intelligence is aware of its limitations. When a demand cannot be fulfilled, AI should be aware of it and gracefully fail. A mechanical backup should be employed after accounting for all potential error conditions. The user should be given a clear indicator when the AI has reached its boundaries so that they can act accordingly. And that brings up the issue’s opposite side – the user also must be conscious of the AI’s constraints. A very unfortunate example of AI’s massive failure was in the US when a pedestrian was killed due to the driver not being aware of the limitations of Uber’s self-driving vehicle system she was using.
4. Communicate Effectively
Smart AI ought to be able to comprehend its users. The AI must be able to properly communicate with its operators in order to achieve this. It should be designed to avoid circumstances in which it requests input from the user but fails to inform them of this requirement. This means that a voice assistant must be able to deal with slang, unintentional remarks, and grammar errors. It should be able to draw on additional sources of information to provide a relevant answer and recall what was stated previously. A competent AI should infer the meaning based on context and prior conversations since there are numerous ways to ask the AI for what you want.
5. Do What is Expected
There is a possibility that AI would act unpredictably due to the fact that it is continually gathering new data and updating how it behaves. Users of AI systems should feel confident in the reliability of the data or results they get. Users should be able to rectify the AI’s errors so that it can learn from them and grow. For instance, when a French chatbot started suggesting suicide, obviously not anticipated by the creators, its algorithms had to be modified.
Considering the instances when AI has unexpectedly acted negatively, it makes perfect sense that AI researchers and the businesses that use the technology should be aware of the potential risks and take precautions to keep away rogue AI. While we must tread with adequate precautions while using AI models, one very obvious thing we should make sure of is the ability to turn off the AI model; basically, a way to kill the machine once and for all if the situation becomes too bad to fix.
On email security in the era of hybrid working
With remote working the future for so many global workforces – or at least some kind of hybrid arrangement – is there an impact on email security we are all missing? Oliver Paterson, director of product management at VIPRE Security, believes so.
“The timeframe that people expect now for you to reply to things is shortened massively,” says Paterson. “This puts additional stress and pressure on individuals, which can then also lead to further mistakes. [Employees] are not as aware if they get an email with a link coming in – and they’re actually more susceptible to clicking on it.”
The cybercriminal’s greatest friend is human error, and distraction makes for a perfect bedfellow. The remote working calendar means that meetings are now held in virtual rooms, instead of face-to-face. A great opportunity for a quick catch up on a few emails during a spot of downtime, perhaps? It’s also a great opportunity for an attacker to make you fall for a phishing attack.
“It’s really about putting in the forefront there that email is the major first factor when we talk about data breaches, and anything around cyberattacks and ransomware being deployed on people’s machines,” Paterson says around education. “We just need to be very aware that even though we think these things are changing, [you] need to add a lot more security, methods and the tactics that people are using to get into your business is still very similar.
“The attacks may be more sophisticated, but the actual attack vector is the same as it was 10-15 years ago.”
This bears true in the statistics. The Anti-Phishing Working Group (APWG) found in its Phishing Activity Trends Report (pdf) in February that attacks hit an all-time high in 2021. Attacks had tripled since early 2020 – in other words, since the pandemic began.
VIPRE has many solutions to this age-old problem, and the email security product side of the business comes primarily under Paterson’s remit. One such product is VIPRE SafeSend, which focuses on misaddressed emails and prevents data leakage. “Everyone’s sent an email to the wrong person at some point in their life,” says Paterson. “It just depends how serious that’s been.”
Paterson notes one large FMCG brand, where a very senior C-level executive had the same name as someone else in the business much lower down. Naturally, plenty of emails went to the wrong place. “You try and get people to be uber-careful, but we’ve got technology solutions to help with those elements as well now,” says Paterson. “It’s making sure that businesses are aware of that, then also having it in one place.”
Another part of the product portfolio is with EDR (endpoint detection and response). The goal for VIPRE is to ‘take the complexities out of EDR management for small to medium-sized businesses and IT teams.’ Part of this is understanding what organisations really want.
The basic knowledge is there, as many organisational surveys will show. Take a study from the Enterprise Security Group (ESG) released in October in terms of ransomware preparedness. Respondents cited network security (43%), backup infrastructure security (40%), endpoint (39%), email (36%) and data encryption (36%) as key prevention areas. Many security vendors offer this and much more – but how difficult is it to filter out the noise?
“People understand they need an endpoint solution, and an email security solution. There’s a lot of competitors out there and they’re all shouting about different things,” says Paterson. “So it’s really getting down to the nitty gritty of what they actually need as a business. That’s where we at VIPRE try to make it as easy as possible for clients.
“A lot of companies do EDR at the moment, but what we’ve tried to do is get it down to the raw elements that every business will need, and maybe not all the bells and whistles that probably 99% of organisations aren’t going to need,” Paterson adds.
“We’re very much a company that puts a lot of emphasis on our clients and partners, where we treat everyone as an individual business. We get a lot of comments [from customers] that some of the biggest vendors in there just treat them as a number.”
Paterson is speaking at the Cyber Security & Cloud Expo Global, in London on December 1-2 around the rising threat of ransomware, and how the security industry evolves alongside this threat. Having a multi-layered approach will be a cornerstone of Paterson’s message, and his advice to businesses is sound.
“Take a closer look at those areas, those threat vectors, the way that they are coming into the business, and make sure that you are putting those industry-level systems in place,” he says. “A lot of businesses can get complacent and just continue renewing the same thing over and over again, without realising there are new features and additions. Misdelivery of email is a massive one – I would say the majority of businesses don’t have anything in place for it.
“Ask ‘where are the risk areas for your business?’ and understand those more, and then make sure to put those protection layers in place to help with things like ransomware attacks and other elements.”
Want to learn more about cybersecurity and the cloud from industry leaders? Check out Cyber Security & Cloud Expo taking place in Amsterdam, California, and London.
Explore other upcoming enterprise technology events and webinars powered by TechForge here.
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