We Asked Chatbots About Home Security: Here's Why You Can't Trust Them
I've been a proponent of useful AI in home security, where it's holding conversations for us, identifying packages, learning to recognize important objects and searching our video histories to answer questions. But that doesn't mean you should pop open ChatGPT and start asking it security questions.
Generative and conversational AI tools have their uses, but it's a bad idea to ask any chatbot about your safety, home security, or threats to your house. We tried -- and it's unnerving how much they get wrong or can't help with.
There are good reasons for this: Even the best LLMs, or large language models, still hallucinate information from the patterns they've gleaned. That's especially a problem in smart home tech, where tech specs, models, compatibility, vulnerabilities and updates shift so frequently. That means its easy for ChatGPT to get confused about what's right, current or even real.
Let's look at a few of the biggest mistakes, so you can see what I mean.
Asking a chatbot about specific security technology is always a risky business, and nothing illustrates that quite so well as this popular Reddit story about a chat AI that told the user a Tesla could access their "home security systems." That's not true -- it's probably a hallucination based on Tesla's HomeLink service, which lets you open compatible garage doors. Services like Google Gemini also suffer from hallucinations, which can make the details hard to trust.
While AI can write anything from essays to phishing emails (don't do that), it still gets information wrong, which can lead to unfounded privacy concerns. Interestingly, when I asked ChatGPT what Teslas could connect to and monitor, it didn't make the same mistake, but it did skip features like HomeLink, so you still aren't getting the full picture. And that's just the start.
ChatGPT and other LLMs also struggle to assimilate real-time information and use it to provide advice. That's especially noticeable during natural disasters like wildfires, floods or hurricanes. As hurricane Milton was bearing down this month, I queried ChatGPT about whether my home was in danger and where Milton was going to hit. Though, thankfully, the chatbot avoided wrong answers, it was unable to give me any advice except to consult local weather channels and emergency services.
Don't waste time on that when your home may be in trouble. Instead of turning to AI for a quick answer, consult weather apps and software like Watch Duty; up-to-date satellite imagery; and local news.
It would be nice if AI chatbots could provide a summary of a brand's history with security breaches and whether there are any red flags about purchasing the brand's products. Unfortunately, they don't seem capable of that yet, so you can't really trust what they have to say about security companies.
For example, when I asked ChatGPT if Ring had suffered any security breaches, it mentioned that Ring had experienced security incidents, but not when (before 2018), which is a vital piece of information. It also missed key developments, including the completion of Ring's payout to affected customers this year and Ring's 2024 policy reversal that made cloud data harder for police to access.
When I asked about Wyze, which CNET isn't currently recommending, ChatGPT said it was a "good option" for home security but mentioned it suffered a data breach in 2019 that exposed user data. But it didn't mention that Wyze had exposed databases and video files in 2022, then vulnerabilities in 2023 and again in 2024 that let users access private home videos that weren't their own. So while summaries are nice, you certainly aren't getting the full picture when it comes to security history or if brands are safe to trust.
Read more: We Asked a Top Criminologist How Burglars Choose Homes
Another common home security question I see is about the need for subscriptions to use security systems or home cameras. Some people don't want to pay ongoing subscriptions, or they want to make sure what they get is worth it. Though chatbots can give lots of recipe specifics, they aren't any help here.
When I questioned ChatGPT about whether Reolink requires subscriptions, it couldn't give me any specifics, saying many products don't require subscriptions for basic features but that Reolink "may offer subscriptions plans" for advanced features. I tried to narrow it down with a question about the Reolink Argus 4 Pro, but again ChatGPT remained vague about some features being free and some possibly needing subscriptions. As answers go, these were largely useless.
Meanwhile, a trip to CNET's guide on security camera subscriptions or Reolink's own subscriptions page shows that Reolink offers both Classic and Upgraded tier subscriptions specifically for LTE cameras, starting at $6 to $7 per month, depending on how many cameras you want to support, and going up to $15 to $25 for extra cloud storage and rich notifications/smart alerts. Finding those answers takes less time than asking ChatGPT, and you get real numbers to work with.
Best DIY Home Security Systems of 2024
See at CNET
As the famous detective said, "Just one more thing." If you do ever query a chatbot about home security, never give it any personal information, like your home address, your name, your living situation or any type of payment info. AIs like ChatGPT have had bugs before that allowed other users to spy on private data like that.
Additionally, LLM privacy policies can always be updated or left vague enough to allow for profiling and the sale of user data they collect. The scraping of data from social media is bad enough, you really don't want to hand personal details over directly to a popular AI service.
Be careful what data you provide as part of a question, and even how you phrase your query, because there's always someone eager to take advantage of whatever data you let slip. If you think you've already given out your address a few too many times online, we have a guide on how you can help fix that.
Read more: Your Private Data Is All Over the Internet. Here's What You Can Do About It
For more information, check out whether you should pay for more-advanced ChatGPT features, and take a look at our in-depth review of Google Gemini and our coverage of the latest on Apple Intelligence.
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Forbes
36 minutes ago
- Forbes
Doing The Work With Frontier Models: I'll Talk To AI
Artificial Intelligence processor unit. Powerful Quantum AI component on PCB motherboard with data ... More transfers. Within the industry, where people talk about the specifics of how LLMs work, they often use the term 'frontier models.' But if you're not connected to this business, you probably don't really know what that means. You can intuitively apply the word 'frontier' to know that these are the biggest and best new systems that companies are pushing. Another way to describe frontier models is as 'cutting-edge' AI systems that are broad in purpose, and overall frameworks for improving AI capabilities. When asked, ChatGPT gives us three criteria – massive data sets, compute resources, and sophisticated architectures. Here are some key characteristics of frontier models to help you flush out your vision of how these models work: First, there is multimodality, where frontier models are likely to support non-text inputs and outputs – things like image, video or audio. Otherwise, they can see and hear – not just read and write. Another major characteristic is zero-shot learning, where the system is more capable with less prompting. And then there's that agent-like behavior that has people talking about the era of 'agentic AI.' If you want to play 'name that model' and get specific about what companies are moving this research forward, you could say that GPT 4o from OpenAI represents one such frontier model, with multi-modality and real-time inference. Or you could tout the capabilities of Gemini 1.5, which is also multimodal, with decent context. And you can point to any number of other examples of companies doing this kind of research well…but also: what about digging into the build of these systems? At a recent panel at Imagination in Action, a team of experts analyzed what it takes to work in this part of the AI space and create these frontier models The panel moderator, Peter Grabowski, introduced two related concepts for frontier models – quality versus sufficiency, and multimodality. 'We've seen a lot of work in text models,' he said. 'We've seen a lot of work on image models. We've seen some work in video, or images, but you can easily imagine, this is just the start of what's to come.' Douwe Kiela, CEO of Contextual AI, pointed out that frontier models need a lot of resources, noting that 'AI is a very resource-intensive endeavor.' 'I see the cost versus quality as the frontier, and the models that actually just need to be trained on specific data, but actually the robustness of the model is there,' said Lisa Dolan, managing director of Link Ventures (I am also affiliated with Link.) 'I think there's still a lot of headroom for growth on the performance side of things,' said Vedant Agrawal, VP of Premji Invest. Agrawal also talked about the value of using non-proprietary base models. 'We can take base models that other people have trained, and then make them a lot better,' he said. 'So we're really focused on all the all the components that make up these systems, and how do we (work with) them within their little categories?' The panel also discussed benchmarking as a way to measure these frontier systems. 'Benchmarking is an interesting question, because it is single-handedly the best thing and the worst thing in the world of research,' he said. 'I think it's a good thing because everyone knows the goal posts and what they're trying to work towards, and it's a bad thing because you can easily game the system.' How does that 'gaming the system' work? Agrawal suggested that it can be hard to really use benchmarks in a concrete way. 'For someone who's not deep in the research field, it's very hard to look at a benchmarking table and say, 'Okay, you scored 99.4 versus someone else scored 99.2,'' he said. 'It's very hard to contextualize what that .2% difference really means in the real world.' 'We look at the benchmarks, because we kind of have to report on them, but there's massive benchmark fatigue, so nobody even believes it,' Dolan said. Later, there was some talk about 10x systems, and some approaches to collecting and using data: · Identifying contractual business data · Using synthetic data · Teams of annotators When asked about the future of these systems, the panel return these three concepts: · AI agents · Cross-disciplinary techniques · Non-transformer architectures Watch the video to get the rest of the panel's remarks about frontier builds. What Frontier Interfaces Will Look Like Here's a neat little addition – interested in how we will interact with these frontier models in 10 years' time, I put the question to ChatGPT. Here's some of what I got: 'You won't 'open' an app—they'll exist as ubiquitous background agents, responding to voice, gaze, emotion, or task cues … your AI knows you're in a meeting, it reads your emotional state, hears what's being said, and prepares a summary + next actions—before you ask.' That combines two aspects, the mode, and the feel of what new systems are likely to be like. This goes back to the personal approach where we start seeing these models more as colleagues and conversational partners, and less as something that stares at you from a computer screen. In other words, the days of PC-DOS command line systems are over. Windows changed the computer interface from a single-line monochrome system, to something vibrant with colorful windows, reframing, and a tool-based desktop approach. Frontier models are going to do even more for our sense of interface progression. And that's going to be big. Stay tuned.
Yahoo
an hour ago
- Yahoo
Lucid Group Stock: Analysts Fear This 1 Problem Is "More Consequential" Than Investors Think
The EV maker's sales are expected to explode in the coming year. But analysts fear that Lucid Group will face financing troubles. Significantly more funding will be needed in the period ahead. 10 stocks we like better than Lucid Group › Lucid Group (NASDAQ: LCID) stock has tremendous long-term growth potential. Its market capitalization right now is under $7 billion -- less than 1% the size of Tesla. This year, sales are expected to grow by 78%. Next year, another 96% sales growth is expected. There's only one problem. According to analysts from Bank of America, there is one emerging risk that is "more consequential" than the market realizes. It's possible that this risk could eventually sink the entire business. After reporting a $397 million fourth-quarter loss this February, Lucid revealed that its longtime CEO, Peter Rawlinson, would be stepping down. It was a surprise to most investors. Rawlinson's comments made the move seem less abrupt than it appeared from an outside perspective, but his absence from the quarterly conference call drew uncertainty. After leading the electric vehicle (EV) maker for 12 years, overseeing the launch of both its Air sedan and Gravity SUV, he simply stated that it was time to move on. "Now that we have successfully launched the Lucid Gravity, I have decided it is finally the right time for me to step aside from my roles at Lucid," Rawlinson explained. Regardless of why Rawlinson stepped aside, many analysts weren't pleased. "We think the departure of Lucid's founder, CEO, and CTO, Peter Rawlinson is much more consequential than understood by the market," Bank of America analyst John Murphy explained after downgrading the stock to underperform. "We now expect product development to stall, consumer demand to be dampened, and anticipate additional funding opportunities could be put at risk." Access to funding is the most critical risk for Lucid. The company now has less than $1.9 billion in cash on the books, yet it posted a $2.4 billion loss over the last 12 months. The company already raised $1.75 billion in late 2024 despite a weak share price, and its shares outstanding have jumped by roughly 30% over the past six months. All in all, Lucid has been racing to raise cash. Yet its cash burn remains very high, share dilution is accelerating, and its share price remains in the dumps, limiting its ability to self-finance without massively diluting shareholders. If capital access is further restrained, as Bank of America believes could happen, the situation could quickly become dire. But could Lucid really go bankrupt over the next 12 months? Like most early stage EV companies, Lucid has been losing money for its entire operating history. It's very expensive to design, build, and scale a capital-intensive business like this. Only until critical scale is achieved, largely through the release of affordable mass market vehicles, do profit margins typically turn positive. Fortunately, Lucid is on the cusp of releasing three new mass market vehicles. Management recently reaffirmed that the first of these should begin production in late 2026, though these timelines are often pushed out. Meanwhile, rapid sales growth from its recently introduced Gravity platform should provide investors with additional confidence. But there's no doubt that time is limited. Some analysts have lost faith in the company, and positive profit margins are still likely years away, leaving the business dependent on outside funding to survive. While it's a very rough estimate, Lucid currently needs around $500 million in cash per quarter to stay afloat. Its current cash pile, plus additional stock sales, should give it at least another year. However, significantly more funding will be needed to get its mass market vehicles into production. That'll likely require sizable share dilution. So while the company may survive, there's no guarantee that long-term investors will benefit. Before you buy stock in Lucid Group, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the for investors to buy now… and Lucid Group wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you'd have $653,702!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $870,207!* Now, it's worth noting Stock Advisor's total average return is 988% — a market-crushing outperformance compared to 172% for the S&P 500. Don't miss out on the latest top 10 list, available when you join . See the 10 stocks » *Stock Advisor returns as of June 9, 2025 Bank of America is an advertising partner of Motley Fool Money. Ryan Vanzo has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Bank of America and Tesla. The Motley Fool has a disclosure policy. Lucid Group Stock: Analysts Fear This 1 Problem Is "More Consequential" Than Investors Think was originally published by The Motley Fool
Yahoo
an hour ago
- Yahoo
After Trump-Musk feud, here's the next issue for Tesla stock
The public name-calling between Elon Musk and President Trump may be over (for now), but the debate around Tesla's (TSLA) stock is only set to heat up as investors digest the upcoming robotaxi launch and likely another weak quarterly report in late July or early August. As one would expect, the very public spat that erupted between Musk and Trump has sent shares of the EV maker on a wild ride. Tesla shares are off by 8% (and a lot more at the height of the sparring session) in June versus a 2% gain for the S&P 500 (^GSPC) as investors fear Trump will take aim at Musk's various lines of business. That's even if the president has cooled his rhetoric on Musk — the president isn't one to forget digs, ever. Musk being out of Trump's inner circle also runs counter to the bull thesis of Tesla's stock following the November election. Remember, Musk being the "first buddy" was supposed to lead to millions of Tesla's driverless cars on the roads and the extension of the Biden administration's EV tax credit, among other pie-in-the-sky predictions that swirled. Good luck with that now, Tesla bulls. But the dustup between the two powerbrokers brings to light a major problem for Tesla's stock as Musk tries to jump-start a sagging EV business by again sleeping inside a factory. There is a BIGLY disconnect between Tesla's valuation and what's happening underneath the surface. For example, Tesla's stock is up 12% since October 2022, but consensus EPS estimates for 2025, 2026, and 2027 have since plunged 77%, 70%, and 71%, respectively, according to new research from JPMorgan auto analyst Ryan Brinkman. You can study Tesla's EPS estimate trends for yourself on the Yahoo Finance platform. The stock is valued at a significant premium to the broader market despite EV tax credits likely going away. Tesla's forward price-to-earnings multiple stands at an eye-popping 166 times compared to 22 times for the S&P 500. Podcast: Why Qualcomm's CEO is pushing hard into the auto market No clue how one can reasonably justify that, given Tesla's weaker fundamentals and as it's heading into at least two years of heavy investment to support robot building and robotaxi operations. The EV tax credit has been a driver of Tesla's sales and profits. EV subsidies represent about 52% of Tesla's current profits, Brinkman estimates. Trump's "big, beautiful bill" that removes the EV tax credit could wipe out these profits for Tesla. Brinkman expects financial estimates to drop in the near term as the impact of the EV subsidy removal becomes clearer. He pointed out that there has been no uplift to medium-term outlooks like sales or earnings due to Musk's Trump connection. Therefore, the post-election Tesla stock rally was "some combination of 'animal spirits', 'speculative fervor', and 'irrational exuberance' allowing for greater investor entertaining of very long-dated bull theses which in our estimation are unlikely to hold up medium-term against the weight of higher-for-longer interest rates and any eventual risk-off shift in the market eliciting sector and thematic rotation," Brinkman said. At some point, the stock has to correct for these elements to the story. Is this finally the moment? I would say this: An electric car eventually runs out of a charge, right? Before you go... Assessing the economy from the beach: By the time you read this, I will have touched down in France for this year's Cannes Lions advertising and media festival. It's an interesting, hot as hell, seriously crowded event that serves up a good pulse on all things advertising and media. But the past few years, it has morphed into more of a CEO and sports celeb scene — making it fertile ground to get clues on the economy, markets, and future investing trends. I have a ton of interviews on tap with market-movers and other fascinating folks, so be sure to stay tuned to Yahoo Finance Monday to Friday. The time is coming: Yahoo Finance's annual Invest conference in November will be here before you know it. New this year is an exclusive dinner the day before the conference for investors, followed by two investor education rooms the next day (along with tons of in-depth interviews). Register for Invest 2025 here. Brian Sozzi is Yahoo Finance's Executive Editor and a member of Yahoo Finance's editorial leadership team. Follow Sozzi on X @BrianSozzi, Instagram, and LinkedIn. Tips on stories? Email Sign in to access your portfolio
