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Is It Too Late To Prevent Potential Harm?

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Is It Too Late To Prevent Potential Harm?

It seems like just yesterday (though it’s been almost six months) since OpenAI launched ChatGPT and began making headlines.

ChatGPT reached 100 million users within three months, making it the fastest-growing application in decades. For comparison, it took TikTok nine months – and Instagram two and a half years – to reach the same milestone.

Now, ChatGPT can utilize GPT-4 along with internet browsing and plugins from brands like Expedia, Zapier, Zillow, and more to answer user prompts.

Big Tech companies like Microsoft have partnered with OpenAI to create AI-powered customer solutions. Google, Meta, and others are building their language models and AI products.

Over 27,000 people – including tech CEOs, professors, research scientists, and politicians – have signed a petition to pause AI development of systems more powerful than GPT-4.

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Now, the question may not be whether the United States government should regulate AI – if it’s not already too late.

The following are recent developments in AI regulation and how they may affect the future of AI advancement.

Federal Agencies Commit To Fighting Bias

Four key U.S. federal agencies – the Consumer Financial Protection Bureau (CFPB), the Department of Justice’s Civil Rights Division (DOJ-CRD), the Equal Employment Opportunity Commission (EEOC), and the Federal Trade Commission (FTC) — issued a statement on the strong commitment to curbing bias and discrimination in automated systems and AI.

These agencies have underscored their intent to apply existing regulations to these emergent technologies to ensure they uphold the principles of fairness, equality, and justice.

  • CFPB, responsible for consumer protection in the financial marketplace, reaffirmed that existing consumer financial laws apply to all technologies, irrespective of their complexity or novelty. The agency has been transparent in its stance that the innovative nature of AI technology cannot be used as a defense for violating these laws.
  • DOJ-CRD, the agency tasked with safeguarding against discrimination in various facets of life, applies the Fair Housing Act to algorithm-based tenant screening services. This exemplifies how existing civil rights laws can be used to automate systems and AI.
  • The EEOC, responsible for enforcing anti-discrimination laws in employment, issued guidance on how the Americans with Disabilities Act applies to AI and software used in making employment decisions.
  • The FTC, which protects consumers from unfair business practices, expressed concern over the potential of AI tools to be inherently biased, inaccurate, or discriminatory. It has cautioned that deploying AI without adequate risk assessment or making unsubstantiated claims about AI could be seen as a violation of the FTC Act.

For example, the Center for Artificial Intelligence and Digital Policy has filed a complaint to the FTC about OpenAI’s release of GPT-4, a product that “is biased, deceptive, and a risk to privacy and public safety.”

Senator Questions AI Companies About Security And Misuse

U.S. Sen. Mark R. Warner sent letters to leading AI companies, including Anthropic, Apple, Google, Meta, Microsoft, Midjourney, and OpenAI.

In this letter, Warner expressed concerns about security considerations in the development and use of artificial intelligence (AI) systems. He requested the recipients of the letter to prioritize these security measures in their work.

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Warner highlighted a number of AI-specific security risks, such as data supply chain issues, data poisoning attacks, adversarial examples, and the potential misuse or malicious use of AI systems. These concerns were set against the backdrop of AI’s increasing integration into various sectors of the economy, such as healthcare and finance, which underscore the need for security precautions.

The letter asked 16 questions about the measures taken to ensure AI security. It also implied the need for some level of regulation in the field to prevent harmful effects and ensure that AI does not advance without appropriate safeguards.

AI companies were asked to respond by May 26, 2023.

The White House Meets With AI Leaders

The Biden-Harris Administration announced initiatives to foster responsible innovation in artificial intelligence (AI), protect citizens’ rights, and ensure safety.

These measures align with the federal government’s drive to manage the risks and opportunities associated with AI.

The White House aims to put people and communities first, promoting AI innovation for the public good and protecting society, security, and the economy.

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Top administration officials, including Vice President Kamala Harris, met with  Alphabet, Anthropic, Microsoft, and OpenAI leaders to discuss this obligation and the need for responsible and ethical innovation.

Specifically, they discussed corporations’ obligation to ensure the safety of LLMs and AI products before public deployment.

New steps would ideally supplement extensive measures already taken by the administration to promote responsible innovation, such as the AI Bill of Rights, the AI Risk Management Framework, and plans for a National AI Research Resource.

Additional actions have been taken to protect users in the AI era, such as an executive order to eliminate bias in the design and use of new technologies, including AI.

The White House noted that the FTC, CFPB, EEOC, and DOJ-CRD have collectively committed to leveraging their legal authority to protect Americans from AI-related harm.

The administration also addressed national security concerns related to AI cybersecurity and biosecurity.

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New initiatives include $140 million in National Science Foundation funding for seven National AI Research Institutes, public evaluations of existing generative AI systems, and new policy guidance from the Office of Management and Budget on using AI by the U.S. government.

The Oversight of AI Hearing Explores AI Regulation

Members of the Subcommittee on Privacy, Technology, and the Law held an Oversight of AI hearing with prominent members of the AI community to discuss AI regulation.

Approaching Regulation With Precision

Christina Montgomery, Chief Privacy and Trust Officer of IBM emphasized that while AI has significantly advanced and is now integral to both consumer and business spheres, the increased public attention it’s receiving requires careful assessment of potential societal impact, including bias and misuse.

She supported the government’s role in developing a robust regulatory framework, proposing IBM’s ‘precision regulation’ approach, which focuses on specific use-case rules rather than the technology itself, and outlined its main components.

Montgomery also acknowledged the challenges of generative AI systems, advocating for a risk-based regulatory approach that doesn’t hinder innovation. She underscored businesses’ crucial role in deploying AI responsibly, detailing IBM’s governance practices and the necessity of an AI Ethics Board in all companies involved with AI.

Addressing Potential Economic Effects Of GPT-4 And Beyond

Sam Altman, CEO of OpenAI, outlined the company’s deep commitment to safety, cybersecurity, and the ethical implications of its AI technologies.

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According to Altman, the firm conducts relentless internal and third-party penetration testing and regular audits of its security controls. OpenAI, he added, is also pioneering new strategies for strengthening its AI systems against emerging cyber threats.

Altman appeared to be particularly concerned about the economic effects of AI on the labor market, as ChatGPT could automate some jobs away. Under Altman’s leadership, OpenAI is working with economists and the U.S. government to assess these impacts and devise policies to mitigate potential harm.

Altman mentioned their proactive efforts in researching policy tools and supporting programs like Worldcoin that could soften the blow of technological disruption in the future, such as modernizing unemployment benefits and creating worker assistance programs. (A fund in Italy, meanwhile, recently reserved 30 million euros to invest in services for workers most at risk of displacement from AI.)

Altman emphasized the need for effective AI regulation and pledged OpenAI’s continued support in aiding policymakers. The company’s goal, Altman affirmed, is to assist in formulating regulations that both stimulate safety and allow broad access to the benefits of AI.

He stressed the importance of collective participation from various stakeholders, global regulatory strategies, and international collaboration for ensuring AI technology’s safe and beneficial evolution.

Exploring The Potential For AI Harm

Gary Marcus, Professor of Psychology and Neural Science at NYU, voiced his mounting concerns over the potential misuse of AI, particularly powerful and influential language models like GPT-4.

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He illustrated his concern by showcasing how he and a software engineer manipulated the system to concoct an entirely fictitious narrative about aliens controlling the US Senate.

This illustrative scenario exposed the danger of AI systems convincingly fabricating stories, raising alarm about the potential for such technology to be used in malicious activities – such as election interference or market manipulation.

Marcus highlighted the inherent unreliability of current AI systems, which can lead to serious societal consequences, from promoting baseless accusations to providing potentially harmful advice.

An example was an open-source chatbot appearing to influence a person’s decision to take their own life.

Marcus also pointed out the advent of ‘datocracy,’ where AI can subtly shape opinions, possibly surpassing the influence of social media. Another alarming development he brought to attention was the rapid release of AI extensions, like OpenAI’s ChatGPT plugins and the ensuing AutoGPT, which have direct internet access, code-writing capability, and enhanced automation powers, potentially escalating security concerns.

Marcus closed his testimony with a call for tighter collaboration between independent scientists, tech companies, and governments to ensure AI technology’s safety and responsible use. He warned that while AI presents unprecedented opportunities, the lack of adequate regulation, corporate irresponsibility, and inherent unreliability might lead us into a “perfect storm.”

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Can We Regulate AI?

As AI technologies push boundaries, calls for regulation will continue to mount.

In a climate where Big Tech partnerships are on the rise and applications are expanding, it rings an alarm bell: Is it too late to regulate AI?

Federal agencies, the White House, and members of Congress will have to continue investigating the urgent, complex, and potentially risky landscape of AI while ensuring promising AI advancements continue and Big Tech competition isn’t regulated entirely out of the market.


Featured image: Katherine Welles/Shutterstock



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Measuring Content Impact Across The Customer Journey

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Measuring Content Impact Across The Customer Journey

Understanding the impact of your content at every touchpoint of the customer journey is essential – but that’s easier said than done. From attracting potential leads to nurturing them into loyal customers, there are many touchpoints to look into.

So how do you identify and take advantage of these opportunities for growth?

Watch this on-demand webinar and learn a comprehensive approach for measuring the value of your content initiatives, so you can optimize resource allocation for maximum impact.

You’ll learn:

  • Fresh methods for measuring your content’s impact.
  • Fascinating insights using first-touch attribution, and how it differs from the usual last-touch perspective.
  • Ways to persuade decision-makers to invest in more content by showcasing its value convincingly.

With Bill Franklin and Oliver Tani of DAC Group, we unravel the nuances of attribution modeling, emphasizing the significance of layering first-touch and last-touch attribution within your measurement strategy. 

Check out these insights to help you craft compelling content tailored to each stage, using an approach rooted in first-hand experience to ensure your content resonates.

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Whether you’re a seasoned marketer or new to content measurement, this webinar promises valuable insights and actionable tactics to elevate your SEO game and optimize your content initiatives for success. 

View the slides below or check out the full webinar for all the details.

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How to Find and Use Competitor Keywords

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How to Find and Use Competitor Keywords

Competitor keywords are the keywords your rivals rank for in Google’s search results. They may rank organically or pay for Google Ads to rank in the paid results.

Knowing your competitors’ keywords is the easiest form of keyword research. If your competitors rank for or target particular keywords, it might be worth it for you to target them, too.

There is no way to see your competitors’ keywords without a tool like Ahrefs, which has a database of keywords and the sites that rank for them. As far as we know, Ahrefs has the biggest database of these keywords.

How to find all the keywords your competitor ranks for

  1. Go to Ahrefs’ Site Explorer
  2. Enter your competitor’s domain
  3. Go to the Organic keywords report

The report is sorted by traffic to show you the keywords sending your competitor the most visits. For example, Mailchimp gets most of its organic traffic from the keyword “mailchimp.”

Mailchimp gets most of its organic traffic from the keyword, “mailchimp”.Mailchimp gets most of its organic traffic from the keyword, “mailchimp”.

Since you’re unlikely to rank for your competitor’s brand, you might want to exclude branded keywords from the report. You can do this by adding a Keyword > Doesn’t contain filter. In this example, we’ll filter out keywords containing “mailchimp” or any potential misspellings:

Filtering out branded keywords in Organic keywords reportFiltering out branded keywords in Organic keywords report

If you’re a new brand competing with one that’s established, you might also want to look for popular low-difficulty keywords. You can do this by setting the Volume filter to a minimum of 500 and the KD filter to a maximum of 10.

Finding popular, low-difficulty keywords in Organic keywordsFinding popular, low-difficulty keywords in Organic keywords

How to find keywords your competitor ranks for, but you don’t

  1. Go to Competitive Analysis
  2. Enter your domain in the This target doesn’t rank for section
  3. Enter your competitor’s domain in the But these competitors do section
Competitive analysis reportCompetitive analysis report

Hit “Show keyword opportunities,” and you’ll see all the keywords your competitor ranks for, but you don’t.

Content gap reportContent gap report

You can also add a Volume and KD filter to find popular, low-difficulty keywords in this report.

Volume and KD filter in Content gapVolume and KD filter in Content gap

How to find keywords multiple competitors rank for, but you don’t

  1. Go to Competitive Analysis
  2. Enter your domain in the This target doesn’t rank for section
  3. Enter the domains of multiple competitors in the But these competitors do section
Competitive analysis report with multiple competitorsCompetitive analysis report with multiple competitors

You’ll see all the keywords that at least one of these competitors ranks for, but you don’t.

Content gap report with multiple competitorsContent gap report with multiple competitors

You can also narrow the list down to keywords that all competitors rank for. Click on the Competitors’ positions filter and choose All 3 competitors:

Selecting all 3 competitors to see keywords all 3 competitors rank forSelecting all 3 competitors to see keywords all 3 competitors rank for
  1. Go to Ahrefs’ Site Explorer
  2. Enter your competitor’s domain
  3. Go to the Paid keywords report
Paid keywords reportPaid keywords report

This report shows you the keywords your competitors are targeting via Google Ads.

Since your competitor is paying for traffic from these keywords, it may indicate that they’re profitable for them—and could be for you, too.

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You know what keywords your competitors are ranking for or bidding on. But what do you do with them? There are basically three options.

1. Create pages to target these keywords

You can only rank for keywords if you have content about them. So, the most straightforward thing you can do for competitors’ keywords you want to rank for is to create pages to target them.

However, before you do this, it’s worth clustering your competitor’s keywords by Parent Topic. This will group keywords that mean the same or similar things so you can target them all with one page.

Here’s how to do that:

  1. Export your competitor’s keywords, either from the Organic Keywords or Content Gap report
  2. Paste them into Keywords Explorer
  3. Click the “Clusters by Parent Topic” tab
Clustering keywords by Parent TopicClustering keywords by Parent Topic

For example, MailChimp ranks for keywords like “what is digital marketing” and “digital marketing definition.” These and many others get clustered under the Parent Topic of “digital marketing” because people searching for them are all looking for the same thing: a definition of digital marketing. You only need to create one page to potentially rank for all these keywords.

Keywords under the cluster of "digital marketing"Keywords under the cluster of "digital marketing"

2. Optimize existing content by filling subtopics

You don’t always need to create new content to rank for competitors’ keywords. Sometimes, you can optimize the content you already have to rank for them.

How do you know which keywords you can do this for? Try this:

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  1. Export your competitor’s keywords
  2. Paste them into Keywords Explorer
  3. Click the “Clusters by Parent Topic” tab
  4. Look for Parent Topics you already have content about

For example, if we analyze our competitor, we can see that seven keywords they rank for fall under the Parent Topic of “press release template.”

Our competitor ranks for seven keywords that fall under the "press release template" clusterOur competitor ranks for seven keywords that fall under the "press release template" cluster

If we search our site, we see that we already have a page about this topic.

Site search finds that we already have a blog post on press release templatesSite search finds that we already have a blog post on press release templates

If we click the caret and check the keywords in the cluster, we see keywords like “press release example” and “press release format.”

Keywords under the cluster of "press release template"Keywords under the cluster of "press release template"

To rank for the keywords in the cluster, we can probably optimize the page we already have by adding sections about the subtopics of “press release examples” and “press release format.”

3. Target these keywords with Google Ads

Paid keywords are the simplest—look through the report and see if there are any relevant keywords you might want to target, too.

For example, Mailchimp is bidding for the keyword “how to create a newsletter.”

Mailchimp is bidding for the keyword “how to create a newsletter”Mailchimp is bidding for the keyword “how to create a newsletter”

If you’re ConvertKit, you may also want to target this keyword since it’s relevant.

If you decide to target the same keyword via Google Ads, you can hover over the magnifying glass to see the ads your competitor is using.

Mailchimp's Google Ad for the keyword “how to create a newsletter”Mailchimp's Google Ad for the keyword “how to create a newsletter”

You can also see the landing page your competitor directs ad traffic to under the URL column.

The landing page Mailchimp is directing traffic to for “how to create a newsletter”The landing page Mailchimp is directing traffic to for “how to create a newsletter”

Learn more

Check out more tutorials on how to do competitor keyword analysis:

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Google Confirms Links Are Not That Important

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Google confirms that links are not that important anymore

Google’s Gary Illyes confirmed at a recent search marketing conference that Google needs very few links, adding to the growing body of evidence that publishers need to focus on other factors. Gary tweeted confirmation that he indeed say those words.

Background Of Links For Ranking

Links were discovered in the late 1990’s to be a good signal for search engines to use for validating how authoritative a website is and then Google discovered soon after that anchor text could be used to provide semantic signals about what a webpage was about.

One of the most important research papers was Authoritative Sources in a Hyperlinked Environment by Jon M. Kleinberg, published around 1998 (link to research paper at the end of the article). The main discovery of this research paper is that there is too many web pages and there was no objective way to filter search results for quality in order to rank web pages for a subjective idea of relevance.

The author of the research paper discovered that links could be used as an objective filter for authoritativeness.

Kleinberg wrote:

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“To provide effective search methods under these conditions, one needs a way to filter, from among a huge collection of relevant pages, a small set of the most “authoritative” or ‘definitive’ ones.”

This is the most influential research paper on links because it kick-started more research on ways to use links beyond as an authority metric but as a subjective metric for relevance.

Objective is something factual. Subjective is something that’s closer to an opinion. The founders of Google discovered how to use the subjective opinions of the Internet as a relevance metric for what to rank in the search results.

What Larry Page and Sergey Brin discovered and shared in their research paper (The Anatomy of a Large-Scale Hypertextual Web Search Engine – link at end of this article) was that it was possible to harness the power of anchor text to determine the subjective opinion of relevance from actual humans. It was essentially crowdsourcing the opinions of millions of website expressed through the link structure between each webpage.

What Did Gary Illyes Say About Links In 2024?

At a recent search conference in Bulgaria, Google’s Gary Illyes made a comment about how Google doesn’t really need that many links and how Google has made links less important.

Patrick Stox tweeted about what he heard at the search conference:

” ‘We need very few links to rank pages… Over the years we’ve made links less important.’ @methode #serpconf2024″

Google’s Gary Illyes tweeted a confirmation of that statement:

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“I shouldn’t have said that… I definitely shouldn’t have said that”

Why Links Matter Less

The initial state of anchor text when Google first used links for ranking purposes was absolutely non-spammy, which is why it was so useful. Hyperlinks were primarily used as a way to send traffic from one website to another website.

But by 2004 or 2005 Google was using statistical analysis to detect manipulated links, then around 2004 “powered-by” links in website footers stopped passing anchor text value, and by 2006 links close to the words “advertising” stopped passing link value, links from directories stopped passing ranking value and by 2012 Google deployed a massive link algorithm called Penguin that destroyed the rankings of likely millions of websites, many of which were using guest posting.

The link signal eventually became so bad that Google decided in 2019 to selectively use nofollow links for ranking purposes. Google’s Gary Illyes confirmed that the change to nofollow was made because of the link signal.

Google Explicitly Confirms That Links Matter Less

In 2023 Google’s Gary Illyes shared at a PubCon Austin that links were not even in the top 3 of ranking factors. Then in March 2024, coinciding with the March 2024 Core Algorithm Update, Google updated their spam policies documentation to downplay the importance of links for ranking purposes.

Google March 2024 Core Update: 4 Changes To Link Signal

The documentation previously said:

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“Google uses links as an important factor in determining the relevancy of web pages.”

The update to the documentation that mentioned links was updated to remove the word important.

Links are not just listed as just another factor:

“Google uses links as a factor in determining the relevancy of web pages.”

At the beginning of April Google’s John Mueller advised that there are more useful SEO activities to engage on than links.

Mueller explained:

“There are more important things for websites nowadays, and over-focusing on links will often result in you wasting your time doing things that don’t make your website better overall”

Finally, Gary Illyes explicitly said that Google needs very few links to rank webpages and confirmed it.

Why Google Doesn’t Need Links

The reason why Google doesn’t need many links is likely because of the extent of AI and natural language undertanding that Google uses in their algorithms. Google must be highly confident in its algorithm to be able to explicitly say that they don’t need it.

Way back when Google implemented the nofollow into the algorithm there were many link builders who sold comment spam links who continued to lie that comment spam still worked. As someone who started link building at the very beginning of modern SEO (I was the moderator of the link building forum at the #1 SEO forum of that time), I can say with confidence that links have stopped playing much of a role in rankings beginning several years ago, which is why I stopped about five or six years ago.

Read the research papers

Authoritative Sources in a Hyperlinked Environment – Jon M. Kleinberg (PDF)

The Anatomy of a Large-Scale Hypertextual Web Search Engine

Featured Image by Shutterstock/RYO Alexandre

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