With over 50,000 downloads, the screen recording app was initially legitimate, but the malicious functionality was later implemented

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In case you don’t have enough to worry about, someone has built a credible handwriting machine:

This is still a work in progress, but the project seeks to solve one of the biggest problems with other homework machines, such as this one that I covered a few months ago after it blew up on social media. The problem with most homework machines is that they’re too perfect. Not only is their content output too well-written for most students, but they also have perfect grammar and punctuation ­ something even we professional writers fail to consistently achieve. Most importantly, the machine’s “handwriting” is too consistent. Humans always include small variations in their writing, no matter how honed their penmanship.

Devadath is on a quest to fix the issue with perfect penmanship by making his machine mimic human handwriting. Even better, it will reflect the handwriting of its specific user so that AI-written submissions match those written by the student themselves.

Like other machines, this starts with asking ChatGPT to write an essay based on the assignment prompt. That generates a chunk of text, which would normally be stylized with a script-style font and then output as g-code for a pen plotter. But instead, Devadeth created custom software that records examples of the user’s own handwriting. The software then uses that as a font, with small random variations, to create a document image that looks like it was actually handwritten.

Watch the video.

My guess is that this is another detection/detection avoidance arms race.

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Increased awareness of data privacy issues has reduced trust in organizations, according to the survey

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The content of this post is solely the responsibility of the author.  AT&T does not adopt or endorse any of the views, positions, or information provided by the author in this article. 

Artificial intelligence is the hottest topic in tech today. AI algorithms are capable of breaking down massive amounts of data in the blink of an eye and have the potential to help us all lead healthier, happier lives.

The power of machine learning means that AI-integrated telehealth services are on the rise, too. Almost every progressive provider today uses some amount of AI to track patients’ health data, schedule appointments, or automatically order medicine.

However, AI-integrated telehealth may pose a cybersecurity risk. New technology is vulnerable to malicious actors and complex AI systems are largely reliant on a web of interconnected Internet of Things (IoT) devices.

Before adopting AI, providers and patients must understand the unique opportunities and challenges that come with automation and algorithms.

Improving the healthcare consumer journey

Effective telehealth care is all about connecting patients with the right provider at the right time. Folks who need treatment can’t be delayed by bureaucratic practices or burdensome red tape. AI can improve the patient journey by automating monotonous tasks and improving the efficiency of customer identity and access management (CIAM) software.

CIAM software that uses AI can utilize digital identity solutions to automate the registration and patient service process. This is important, as most patients say that they’d rather resolve their own questions and queries on their own before speaking to a service agent. Self-service features even allow patients to share important third-party data with telehealth systems via IoT tech like smartwatches.

AI-integrated CIAM software is interoperable, too. This means that patients and providers can connect to the CIAM using omnichannel pathways. As a result, users can use data from multiple systems within the same telehealth digital ecosystem. However, this omnichannel approach to the healthcare consumer journey still needs to be HIPAA compliant and protect patient privacy.

Medicine and diagnoses

Misdiagnoses are more common than most people realize. In the US, 12 million people are misdiagnosed every year. Diagnoses may be even more tricky via telehealth, as doctors can’t read patients’ body language or physically inspect their symptoms.

AI can improve the accuracy of diagnoses by leveraging machine learning algorithms during the decision-making process. These programs can be taught how to distinguish between different types of diseases and may point doctors in the right direction. Preliminary findings suggest that this can improve the accuracy of medical diagnoses to 99.5%.

Automated programs can help patients maintain their medicine and re-order repeat prescriptions. This is particularly important for rural patients who are unable to visit the doctor’s office and may have limited time to call in. As a result, telehealth portals that use AI to automate the process help providers close the rural-urban divide.

Ethical considerations

AI has clear benefits in telehealth. However, machine learning programs and automated platforms do put patient data at increased risk of exposure. Additionally, some patients are trying to replace human doctors and therapists altogether with programs like ChatGPT and AI screening apps.

Patients who utilize telehealth apps in lieu of providers must understand the ethical implications of AI healthcare. AI is naturally limited by the data it has been trained on and does not have the same checks and balances as human therapists. Instead of replacing real-life therapy, AI-powered apps should play a back-seat role in providing better, more relevant support.

It’s worth noting that some patients need human interaction. AI may be more efficient, but many patients want to be seen by a real doctor with the ability to empathize with their condition. The human need for connection can even help some patients turn the corner and work towards a healthier, happier life.

AI and Cybersecurity

Cybersecurity is an ever-present concern for healthcare providers across the globe. Patient data is extremely sensitive and cannot be put at risk by faulty algorithms or low-security software. Telehealth apps must be among the most secure platforms to build patient trust and maintain confidentiality.

Unfortunately, the increased adoption of AI means that the risk involved in telehealth is growing. Malicious actors use AI themselves to trawl massive amounts of data and spot security flaws. Telehealth providers must combat scammers and identity fraud by “baking in” security at every step.

Providers can reduce cybersecurity risks by requiring two-step authentication during log-in and timing inactive patients out when they are idle. These simple steps decrease the risk of malicious actors gaining access to patient data.

Additionally, telehealth providers need to regularly maintain and update points of connection. IoT devices are notorious for being weak points in the wider digital ecosystem and may give malicious actors the entry point they need to enter confidential patient portals. Providers can reduce the risk of hacking by testing their IoT network regularly and responding rapidly to potential weak points.

Conclusion

AI will improve the accuracy of medical diagnoses and help close the rural-urban healthcare divide. However, AI-integrated telehealth services may put some user data at risk. Providers can firm up their patient portals and CIAM software by utilizing common-sense procedures like two-factor authentication and hiring a team of cybersecurity specialists to reduce the risk of an attack.

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The Indian manufacturing plant responsible for manufacturing Suzuki motorcycles has been forced to shut down following a cyber attack, with the loss of an estimated 20,000 vehicles.

Read more in my article on the Hot for Security blog.

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