insights.manageengine.com Open in urlscan Pro
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3 forms found in the DOM

GET https://insights.manageengine.com/

<form role="search" method="get" id="searchform" action="https://insights.manageengine.com/">
  <div><label class="screen-reader-text" for="s">Search for:</label>
    <input type="text" value="" name="s" id="s" placeholder="Search">
    <input type="submit" id="searchsubmit" value="Search">
  </div>
</form>

POST https://insights.manageengine.com/wp-comments-post.php

<form action="https://insights.manageengine.com/wp-comments-post.php" method="post" id="commentform" class="comment-form" novalidate="">
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  <p class="comment-form-comment"><label for="comment">Comment <span class="required">*</span></label> <textarea id="comment" name="comment" cols="45" rows="5" maxlength="65525" required=""></textarea></p>
  <p class="comment-form-author"><label for="author">Name <span class="required">*</span></label> <input id="author" name="author" type="text" value="" size="30" maxlength="245" autocomplete="name" required=""></p>
  <p class="comment-form-email"><label for="email">Email <span class="required">*</span></label> <input id="email" name="email" type="email" value="" size="30" maxlength="100" aria-describedby="email-notes" autocomplete="email" required=""></p>
  <p class="math-captcha-form">
    <label>Captcha<br></label>
    <span><input type="text" size="2" length="2" id="mc-input" class="mc-input" name="mc-value" value="" aria-required="true"> + 51 = 56</span>
  </p>
  <p class="form-submit"><input name="submit" type="submit" id="submit" class="submit" value="Post Comment"> <input type="hidden" name="comment_post_ID" value="2241" id="comment_post_ID">
    <input type="hidden" name="comment_parent" id="comment_parent" value="0">
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  <p class="comment-form-aios-antibot-keys"><input type="hidden" name="ybcuivtr" value="qr69knnexm7z"><input type="hidden" name="twr0kezl" value="z1tezxj8e7zf"><input type="hidden" name="65oy3kqi" value="8uxfk66foxzj"><input type="hidden"
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  <p style="display: none !important;" class="akismet-fields-container" data-prefix="ak_"><label>Δ<textarea name="ak_hp_textarea" cols="45" rows="8" maxlength="100"></textarea></label><input type="hidden" id="ak_js_1" name="ak_js"
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    <script>
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</form>

Name: ME_Insights — POST https://cdev.manageengine.com/server/send-mail/form/me_insights_subscription/addRecord

<form action="https://cdev.manageengine.com/server/send-mail/form/me_insights_subscription/addRecord" colvalue="1" elname="ME_Insights" formtype="1" method="post" name="ME_Insights" tagfor="form" id="newsletter_form" autocomplete="off">
  <input id="nxtURL" name="next-url" type="hidden" value="https://insights.manageengine.com/?msg=success">
  <input name="subject" type="hidden" value="ManageEngine Insight Newsletter">
  <input id="zciplocation" name="iplocation_country" type="hidden" value="" class="zciplocation">
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  <input id="zc-utm_campaign" class="form-control zc_textfield hide_field zc-utm_campaign" maxlength="255" name="utm_campaign" type="text" title="" value="null" style="display:none">
  <input type="hidden" value="12.1" name="version">
  <input name="Type" type="hidden" value="ME Insights" style="display:none">
  <input name="insight_category" type="hidden" value="" style="display:none" id="insight_category">
  <input style="display:none" name="CMleadRef" id="CMleadRef" type="hidden" value="ME_Insights">
  <input style="display:none" name="leadsource" id="leadsource" type="hidden" value="Newsletter">
  <input style="display:none" name="productname" id="productname" type="hidden" value="MEProducts">
  <input style="display:none" name="newsletter_section" id="newsletter_section" type="hidden" value="Newsletter">
  <input id="Pageurl" name="Source_URL" type="hidden"
    value="https://insights.manageengine.com/artificial-intelligence/risks-of-oversharing-with-generative-ai/?utm_source=Zcampaigns&amp;utm_medium=nlmail-news&amp;utm_campaign=ME-Newsletter-D&amp;utm_term=august2023" class="srcurl">
  <div class="clearfix pr">
    <p class="error email-error">Please enter valid email</p>
    <input type="text" id="emailNL" placeholder="Email*" size="32" class="txtfield" name="Email"><select data-countrygdpr="MECountryListing" name="country" id="zccountry" required="required">
      <option value="" name="-Select-" data-ipcode="-Select-">-Select Country-</option>
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      <option value="Botswana" name="Botswana" data-ipcode="BW">Botswana</option>
      <option value="Bouvet Island" name="Bouvet Island" data-ipcode="BV">Bouvet Island</option>
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      <option value="British Virgin Islands" name="British Virgin Islands" data-ipcode="VG">British Virgin Islands</option>
      <option value="British Indian Ocean Territory" name="British Indian Ocean Territory" data-ipcode="IO">British Indian Ocean Territory</option>
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      <option value="Burkina Faso" name="Burkina Faso" data-ipcode="BF">Burkina Faso</option>
      <option value="Burundi" name="Burundi" data-ipcode="BI">Burundi</option>
      <option value="Cabo Verde" name="Cabo Verde" data-ipcode="CV">Cabo Verde</option>
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      <option value="Guatemala" name="Guatemala" data-ipcode="GT">Guatemala</option>
      <option value="Guernsey" name="Guernsey" data-ipcode="GG">Guernsey</option>
      <option value="Guinea" name="Guinea" data-ipcode="GN">Guinea</option>
      <option value="Guinea-Bissau" name="Guinea-Bissau" data-ipcode="GW">Guinea-Bissau</option>
      <option value="Guyana" name="Guyana" data-ipcode="GY">Guyana</option>
      <option value="Haiti" name="Haiti" data-ipcode="HT">Haiti</option>
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Artificial Intelligence


AI’S PRIVACY PANDORA’S BOX: THE RISKS OF OVERSHARING WITH GENERATIVE AI

By Naveena Srinivas Enterprise Analyst, ManageEngine

Published on April 12, 2023

Picture this: you’re scrolling through social media and you come across a video
of a celebrity doing something outrageous. It looks real, but something about it
seems off. It’s only when you read the caption that you realize it’s a deepfake,
created using generative AI. From deepfake videos to ChatGPT-generated
responses, it’s becoming increasingly difficult to tell the difference between
human-made and AI-generated content.

But with this growing reliance on generative AI comes a new concern: the
oversharing of personal data. As we become more comfortable with AI, we might be
unknowingly giving away sensitive information that can be used for purposes we
never intended. We’re in danger of opening a Pandora’s box of privacy breaches,
where our personal information is used in ways we can’t imagine.

The consequences of oversharing personal data can be dire, with risks ranging
from data breaches to the creation of malicious content. While the potential
benefits of generative AI are endless, we need to be mindful of the potential
risks that come with it. In this article, we’ll delve deep into the privacy
breaches and potential risks associated with oversharing personal data with
generative AI, and ways to mitigate the risks and protect yourself and your
data.


WALKING ON A DOUBLE-EDGED SWORD WITH GENERATIVE AI

Generative AI is a technology that uses algorithms to create new and original
content by learning from a dataset. The AI algorithm can generate new content
that is similar to the original data, but not identical. It’s like a chef who
learns the recipe and ingredients of a dish and then uses their creativity to
make new variations of it.

But with great power comes great responsibility, and generative AI is no
exception. The technology requires large amounts of data to work effectively,
which can lead to privacy concerns. The more data you feed into the algorithm,
the more accurate and personalized the content it generates becomes. However,
this also means that personal data is being used, which can be a cause for
concern.



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One of the major privacy concerns with generative AI is the risk of oversharing
personal and confidential information. This happens when individuals or
companies feed large amounts of personal data into the algorithm, which can
include sensitive information such as medical records, financial information,
and personal contacts. If this data falls into the wrong hands, it could be used
for malicious purposes, such as identity theft, cyberattacks, and social
engineering scams. 



For example, generative AI models could be trained on personal data such as
email addresses, names, and social media profiles to create highly convincing
phishing emails. These emails could then be used to trick people into providing
sensitive information such as passwords or credit card details. The volume of
malware scams has visibly grown since the dawn of chatbot technology, and the
technology’s quick adoption in applications raises concerns about data
collection, privacy, and the prevalence of plagiarism and misinformation.

Others are noticing the problem with ChatGPT, a famous generative AI
application, being promoted so quickly and forcefully as well. Leaders in
technology and AI have also raised alerts about this. In 2021, researchers from
Stanford University and the University of Washington demonstrated that it is
possible to use GPT-3, another variant of ChatGPT, to extract personal
information such as names, phone numbers, and email addresses from text. 

Did you know?

A study by Home Security Heroes shows that a new AI password cracker can
decipher 71% of common passwords in less than a day.


EXPLORING WAYS TO DEFEND CONFIDENTIALITY

Generative AI can offer many benefits, but we cannot turn a blind eye to the
chance of personal information leaking from training data, making it difficult
to secure it. A relational database can limit access to a particular table with
personal information, but an AI can be queried in dozens of different ways.
Attackers will quickly learn how to ask the right questions to obtain sensitive
data. Teaching an AI to protect private data is something we don’t yet
understand.

To protect yourself and your data from generative AI, it is important to be
aware of what data you’re sharing and use strong and unique passwords to protect
your data. Limit access to devices, keep software up to date, and use
privacy-preserving tools like VPNs and browser extensions to protect data.
Additionally (and importantly), read the privacy policy carefully to understand
what data is being collected, how it’s being used, and who it’s being shared
with.

Regulators around the world are increasingly taking steps to protect users’ data
from generative AI. Mentioning AI in global legislative proceedings has
increased 6.5 times since 2016, from 1 in 2016 to 37 in 2022. Here are some of
the steps initiated by them:

 1. Data Protection Laws: Governments are enacting or strengthening data
    protection laws to ensure that companies are held accountable for the data
    they collect from users.

 2. Algorithmic Accountability: Regulators are also pushing for greater
    algorithmic accountability, which means holding companies accountable for
    the algorithms they use and ensuring that they are transparent and fair.

 3. Privacy-by-Design: Another approach being taken by regulators is to
    encourage companies to adopt a “privacy-by-design” approach, which means
    designing products and services with privacy in mind from the outset.

 4. Ethical AI Guidelines: Many organizations, including the European Union,
    have developed ethical AI guidelines to help companies navigate the complex
    ethical issues surrounding AI, and ensure that AI is developed and used in
    an ethical and responsible manner.

 5. Regulatory Bodies: Governments are also creating regulatory bodies
    specifically dedicated to overseeing AI, such as the European Commission’s
    High-Level Expert Group on AI, which provides advice and recommendations on
    AI-related policy and regulatory issues.

Overall, the aim of these measures is to ensure that companies using generative
AI are held accountable for the data they collect and use, and that users’
privacy rights are protected. The rush to integrate this technology can result
in data breaches, inaccuracies, and abuse, demonstrating the need for caution
and responsible management.

The Future of Life Institute has released an open letter requesting that AI
laboratories and businesses cease the development of OpenAI systems after
ChatGPT-4. Reputable individuals including Steve Wozniak, the co-founder of
Apple, and Elon Musk, the co-founder of OpenAI, have agreed that progress should
be halted to make sure that people can profit from and enjoy existing systems.

As this article draws to an end, one burning question keeps me up–what will
happen when we humans become so dependent on generative AI that we can no longer
produce new material for training models?

 * AI
 * Artificial intelligence
 * ChatGPT
 * consumer privacy
 * data breach
 * data privacy
 * data security
 * generative AI
 * machine learning
 * technology


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