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Launched just weeks ago, ChatGPT is already threatening to upend how we draft everyday communications like emails, college essays and myriad other forms of writing.

Created by the company OpenAI, ChatGPT is a chatbot that can automatically respond to written prompts in a manner that is sometimes eerily close to human.

But for all the consternation over the potential for humans to be replaced by machines in formats like poetry and sitcom scripts, a far greater threat looms: artificial intelligence replacing humans in the democratic processes—not through voting, but through lobbying.

ChatGPT could automatically compose comments submitted in regulatory processes. It could write letters to the editor for publication in local newspapers. It could comment on news articles, blog entries and social media posts millions of times every day. It could mimic the work that the Russian Internet Research Agency did in its attempt to influence our 2016 elections, but without the agency’s reported multimillion-dollar budget and hundreds of employees.

Automatically generated comments aren’t a new problem. For some time, we have struggled with bots, machines that automatically post content. Five years ago, at least a million automatically drafted comments were believed to have been submitted to the Federal Communications Commission regarding proposed regulations on net neutrality. In 2019, a Harvard undergraduate, as a test, used a text-generation program to submit 1,001 comments in response to a government request for public input on a Medicaid issue. Back then, submitting comments was just a game of overwhelming numbers.

Platforms have gotten better at removing “coordinated inauthentic behavior.” Facebook, for example, has been removing over a billion fake accounts a year. But such messages are just the beginning. Rather than flooding legislators’ inboxes with supportive emails, or dominating the Capitol switchboard with synthetic voice calls, an AI system with the sophistication of ChatGPT but trained on relevant data could selectively target key legislators and influencers to identify the weakest points in the policymaking system and ruthlessly exploit them through direct communication, public relations campaigns, horse trading or other points of leverage.

When we humans do these things, we call it lobbying. Successful agents in this sphere pair precision message writing with smart targeting strategies. Right now, the only thing stopping a ChatGPT-equipped lobbyist from executing something resembling a rhetorical drone warfare campaign is a lack of precision targeting. AI could provide techniques for that as well.

A system that can understand political networks, if paired with the textual-generation capabilities of ChatGPT, could identify the member of Congress with the most leverage over a particular policy area—say, corporate taxation or military spending. Like human lobbyists, such a system could target undecided representatives sitting on committees controlling the policy of interest and then focus resources on members of the majority party when a bill moves toward a floor vote.

Once individuals and strategies are identified, an AI chatbot like ChatGPT could craft written messages to be used in letters, comments—anywhere text is useful. Human lobbyists could also target those individuals directly. It’s the combination that’s important: Editorial and social media comments only get you so far, and knowing which legislators to target isn’t itself enough.

This ability to understand and target actors within a network would create a tool for AI hacking, exploiting vulnerabilities in social, economic and political systems with incredible speed and scope. Legislative systems would be a particular target, because the motive for attacking policymaking systems is so strong, because the data for training such systems is so widely available and because the use of AI may be so hard to detect—particularly if it is being used strategically to guide human actors.

The data necessary to train such strategic targeting systems will only grow with time. Open societies generally make their democratic processes a matter of public record, and most legislators are eager—at least, performatively so—to accept and respond to messages that appear to be from their constituents.

Maybe an AI system could uncover which members of Congress have significant sway over leadership but still have low enough public profiles that there is only modest competition for their attention. It could then pinpoint the SuperPAC or public interest group with the greatest impact on that legislator’s public positions. Perhaps it could even calibrate the size of donation needed to influence that organization or direct targeted online advertisements carrying a strategic message to its members. For each policy end, the right audience; and for each audience, the right message at the right time.

What makes the threat of AI-powered lobbyists greater than the threat already posed by the high-priced lobbying firms on K Street is their potential for acceleration. Human lobbyists rely on decades of experience to find strategic solutions to achieve a policy outcome. That expertise is limited, and therefore expensive.

AI could, theoretically, do the same thing much more quickly and cheaply. Speed out of the gate is a huge advantage in an ecosystem in which public opinion and media narratives can become entrenched quickly, as is being nimble enough to shift rapidly in response to chaotic world events.

Moreover, the flexibility of AI could help achieve influence across many policies and jurisdictions simultaneously. Imagine an AI-assisted lobbying firm that can attempt to place legislation in every single bill moving in the US Congress, or even across all state legislatures. Lobbying firms tend to work within one state only, because there are such complex variations in law, procedure and political structure. With AI assistance in navigating these variations, it may become easier to exert power across political boundaries.

Just as teachers will have to change how they give students exams and essay assignments in light of ChatGPT, governments will have to change how they relate to lobbyists.

To be sure, there may also be benefits to this technology in the democracy space; the biggest one is accessibility. Not everyone can afford an experienced lobbyist, but a software interface to an AI system could be made available to anyone. If we’re lucky, maybe this kind of strategy-generating AI could revitalize the democratization of democracy by giving this kind of lobbying power to the powerless.

However, the biggest and most powerful institutions will likely use any AI lobbying techniques most successfully. After all, executing the best lobbying strategy still requires insiders—people who can walk the halls of the legislature—and money. Lobbying isn’t just about giving the right message to the right person at the right time; it’s also about giving money to the right person at the right time. And while an AI chatbot can identify who should be on the receiving end of those campaign contributions, humans will, for the foreseeable future, need to supply the cash. So while it’s impossible to predict what a future filled with AI lobbyists will look like, it will probably make the already influential and powerful even more so.

This essay was written with Nathan Sanders, and previously appeared in the New York Times.

Edited to Add: After writing this, we discovered that a research group is researching AI and lobbying:

We used autoregressive large language models (LLMs, the same type of model behind the now wildly popular ChatGPT) to systematically conduct the following steps. (The full code is available at this GitHub link: https://github.com/JohnNay/llm-lobbyist.)

1. Summarize official U.S. Congressional bill summaries that are too long to fit into the context window of the LLM so the LLM can conduct steps 2 and 3.
2. Using either the original official bill summary (if it was not too long), or the summarized version:
   1. Assess whether the bill may be relevant to a company based on a company’s description in its SEC 10K filing.
   2. Provide an explanation for why the bill is relevant or not.
   3. Provide a confidence level to the overall answer.
3. If the bill is deemed relevant to the company by the LLM, draft a letter to the sponsor of the bill arguing for changes to the proposed legislation.

Here is the paper.

Written by James Schmidt 

Editor’s Note: We often speak of online scams in our blogs, ones that cost victims hundreds if not thousands of dollars. This account puts a face on one of those scams—along with the personal, financial, and emotional pain that they can leave in their wake. This is the story of “Meredith,” whose aunt “Leslie” fell victim to an emerging form on online elder fraud. Our thanks to James for bringing it forward and to “Meredith’s” family for sharing it, all so others can prevent such scams from happening to them. 

 

“Embarrassing. Simply embarrassing.” She shook her head. “It’s too raw. I can’t talk about it right now. I need time.”   

Her aunt had been scammed. To the tune of $100,000 dollars. My colleague—we both work in the security industry—felt a peculiar sense of loss. 

“I work in this industry. I thought I’d done everything right. I’ve passed on enough warnings to my family and friends to ensure they’d avoid the fate of the scammed.  Simply because I’m in this industry does not imply my circle is always aware of all the threats to them, even if I do my best to teach them.” 

“My mental state, recently, borders on shame; this feeling, you know? How could someone working in my industry have something like this happen to a family member?”  

I told her many people working in other industries cannot control what happens to people in their families even if people in that industry had knowledge that could have helped them or otherwise avoided a problem altogether. 

“I know, but this simply should never have happened! My aunt is one of the smartest, most conscientious people I know, and she fell for this. It’s crazy and I can’t wrap my head around it.” 

My colleague, let’s call her Meredith (not her real name as she’s a bit ashamed to know this happened to a family member), told me the beginnings. 

Let’s call her aunt Leslie. 

Her story unfolds, the overall picture a pastiche of millions of people in the United States today. Her aunt is retired, bored, lonely, and isolated. She feels adrift without something to occupy her time; she was looking for companionship, connections, someone (anyone) to talk to. Her feelings intensified during the pandemic. She morphed into perfect prey for scammers of what is now known as the “Pig Butchering Scam.” 

The term “Pig Butchering” has a visceral and raw feel to it, which falls right in line with how brutal this scam can be. It’s a long con game, where the scammer befriends the victim and encourages them to make small investments through the scammer, which get bigger and bigger over time. The scammer builds trust early with what appear to be small investment wins. None of it is legit. The money goes right into the scammer’s pocket, even as the scammer shows the victim phony financial statements and dashboards to show off the bogus returns. Confidence grows. The scammer wrings even larger sums out of the victim. And then disappears.  

It was a targeted attack that started innocuously enough with a “fake wrong number”. An SMS arrives. A text conversation starts. The scammer then apologizes but tells Leslie someone gave them the number to initiate the text. 

The scammer then uses emotional and psychological techniques to keep Leslie hooked.  “How are you, are you having a nice day?” Leslie, being bored and interested, engages willingly.     

The scammer asks to talk directly, not via text: and a phone conversation ensues.  The scammer proceeds to describe—in very soothing detail—what they are doing, helping people, like Leslie, invest their “hard-earned money” into something that will make them more money, to help them out in retirement. 

Of course, it is too good to be true.  

“The craziest part of all of this is my aunt refuses—to this day—to believe she’s been scammed!” 

She still thinks this scammer is a “friend” even though the entire family is up in arms over this, all of whom beg her aunt to “open her eyes.” 

“My aunt still thinks she’d going to see that money again, or even make some money, which is crazy. The scammers are so good at emotional intelligence; really leveraging heartstrings and psychological makeup of the forlorn in society. My aunt finally agreed to stop sending more money to the scammers, but only after the entire family threatened to cut her off from the rest of the family. It took a lot to get her to stop trusting the scammers.” 

Meredith feels this is doubly sad as the aunt in question is not someone they’d ever imagine would in this predicament. She was always the upright one, always the diligent and hardworking and the best with money. She is smart and savvy and we could never imagine her to be taken by these people and taken so easily. It boggles the mind.” 

She did start to change in the last few years. And the pandemic created a weird situation. Retirement, loneliness from loss of a partner, and the added burden of the pandemic created a perfect storm for her to open herself up to someone willingly, simply for the sake of connection. 

“No one deserves this. It has rocked my family to the core. It is not only about the money, but we’ve found family bonds stretched. She believes these random people, these scammers, more than she believes her own family. Have we been neglectful of our aunt? Does she no longer put her faith in people she knows, rather gives money to complete strangers?” 

Being a security professional does not provide magical protection. We are more aware of scams and scammers, and how they work, and what to look for, and we try to do all we can to keep our family aware of scams out there in the big wide world, but we are human. We fall short. 

Diligence is action. Awareness is action. Education is action. 

We need to be better, all of us, at socializing risky things. We need to consistently educate our family and friends to protect themselves, not only via security software (which everyone should have as default) but by providing tips and tricks and warnings for things we all need to be on the lookout. This is not a one-time thing. The cliché holds true: “If you see something say something.” Repetition helps.  

In today’s world, the need for protecting people’s security, identity, and privacy is critical to keeping them safe. Scammers long stopped focusing on attacking only your computer. Now focus more than ever on YOU: your identity, your privacy, your trust. If they get you there, they soon get your money. 

As for contributing factors to scammers success with their victims, such as loneliness, isolation, and boredom, they all have remedies.  Make connections with your loved ones, especially those easily tagged as vulnerable, those you feel might be at risk. Reach out. It may be hard sometimes due to distance and other factors but make it a point to connect. There is a reason these scammers are succeeding. They are stepping into roles of companions to people who are desperate for connection.   

Most people are greatly saddened at seeing other people being “taken.” Let’s work together to help stop the scammers. 

Look out for each other, and get your people protected! 

Editor’s Closing Note:  

If you or someone you know suspects elder fraud, the following resources can help: 

• In the U.S., the National Elder Fraud Hotline and the Eldercare Locator run by the U.S. Administration on Aging. 
• In the U.K., ActionFraud, run by the National Fraud and Cybercrime Reporting Centre. 
• In Canada, the Canadian Anti-Fraud Centre maintained by the Canadian government. 
• In Australia, Scamwatch, maintained by the Australian Competition and Consumer Commission. 

For further reading on scams and scam prevention, check out the guides in our McAfee Safety Series, which provide in-depth advice on protecting your identity and privacy—and your family from scams. They’re ready to download and share. 

The post A Scam in the Family—How a Close Relative Lost $100,000 to an Elder Scam appeared first on McAfee Blog.