ny mistake with 1,800 letters," he said. "It could not be repaired."

Mr. Sanborn's ideal winning bidder is someone who will hold on to that secret.
He also hopes that person is willing to take over the system of verifying
possible solutions and reviewing those unending emails, possibly through an
automated system.

Here's the auction listing.

** *** ***** ******* *********** *************

AI Agents Need Data Integrity

[2025.08.22] Think of the Web as a digital territory with its own social
contract. In 2014, Tim Berners-Lee called for a "Magna Carta for the Web" to
restore the balance of power between individuals and institutions. This mirrors
the original charter's purpose: ensuring that those who occupy a territory have
a meaningful stake in its governance.

Web 3.0 -- the distributed, decentralized Web of tomorrow -- is finally poised
to change the Internet's dynamic by returning ownership to data creators. This
will change many things about what's often described as the "CIA triad" of
digital security: confidentiality, integrity, and availability. Of those three
features, data integrity will become of paramount importance.

When we have agency in digital spaces, we naturally maintain their integrity --
protecting them from deterioration and shaping them with intention. But in
territories controlled by distant platforms, where we're merely temporary
visitors, that connection frays. A disconnect emerges between those who benefit
from data and those who bear the consequences of compromised integrity. Like
homeowners who care deeply about maintaining the property they own, users in the
Web 3.0 paradigm will become stewards of their personal digital spaces.

This will be critical in a world where AI agents don't just answer our questions
but act on our behalf. These agents may execute financial transactions,
coordinate complex workflows, and autonomously operate critical infrastructure,
making decisions that ripple through entire industries. As digital agents become
more autonomous and interconnected, the question is no longer whether we will
trust AI but what that trust is built upon. In the new age we're entering, the
foundation isn't intelligence or efficiency -- it's integrity.

What Is Data Integrity?

In information systems, integrity is the guarantee that data will not be
modified without authorization, and that all transformations are verifiable
throughout the data's life cycle. While availability ensures that systems are
running and confidentiality prevents unauthorized access, integrity focuses on
whether information is accurate, unaltered, and consistent across systems and
over time.

It's a new idea. The undo button, which prevents accidental data loss, is an
integrity feature. So is the reboot process, which returns a computer to a known
good state. Checksums are an integrity feature; so are verifications of network
transmission. Without integrity, security measures can backfire. Encrypting
corrupted data just locks in errors. Systems that score high marks for
availability but spread misinformation just become amplifiers of risk.

All IT systems require some form of data integrity, but the need for it is
especially pronounced in two areas today. First: Internet of Things devices
interact directly with the physical world, so corrupted input or output can
result in real-world harm. Second: AI systems are only as good as the integrity
of the data they're trained on, and the integrity of their decision-making
processes. If that foundation is shaky, the results will be too.

Integrity manifests in four key areas. The first, input integrity, concerns the
quality and authenticity of data entering a system. When this fails,
consequences can be severe. In 2021, Facebook's global outage was triggered by a
single mistaken command -- an input error missed by automated systems.
Protecting input integrity requires robust authentication of data sources,
cryptographic signing of sensor data, and diversity in input channels for
cross-validation.

The second issue is processing integrity, which ensures that systems transform
inputs into outputs correctly. In 2003, the U.S.-Canada blackout affected 55
million people when a control-room process failed to refresh properly, resulting
in damages exceeding US $6 billion. Safeguarding processing integrity means
formally verifying algorithms, cryptographically protecting models, and
monitoring systems for anomalous behavior.

Storage integrity covers the correctness of information as it's stored and
communicated. In 2023, the Federal Aviation Administration was forced to halt
all U.S. departing flights because of a corrupted database file. Addressing this
risk requires cryptographic approaches that make any modification
computationally infeasible without detection, distributed storage systems to
prevent single points of failure, and rigorous backup procedures.

Finally, contextual integrity addresses the appropriate flow of information
according to the norms of its larger context. It's not enough for data to be
accurate; it must also be used in ways that respect expectations and boundaries.
For example, if a smart speaker listens in on casual family conversations and
uses the data to build advertising profiles, that action would violate the
expected boundaries of data collection. Preserving contextual integrity requires
clear data-governance policies, principles that limit the use of data to its
intended purposes, and mechanisms for enforcing information-flow constraints.

As AI systems increasingly make critical decisions with reduced human oversight,
all these dimensions of integrity become critical.

The Need for Integrity in Web 3.0

As the digital landscape has shifted from Web 1.0 to Web 2.0 and now evolves
toward Web 3.0, we've seen each era bring a different emphasis in the CIA triad
of confidentiality, integrity, and availability.

Returning to our home metaphor: When simply having shelter is what matters most,
availability takes priority -- the house must exist and be functional. Once that
foundation is secure, confidentiality becomes important -- you need locks on
your doors to keep others out. Only after these basics are established do you
begin to consider integrity, to ensure that what's inside the house remains
trustworthy, unaltered, and consistent over time.

Web 1.0 of the 1990s prioritized making information available. Organizations
digitized their content, putting it out there for anyone to access. In Web 2.0,
the Web of today, platforms for e-commerce, social media, and cloud computing
prioritize confidentiality, as personal data has become the Internet's currency.

Somehow, integrity was largely lost along the way. In our current Web
architecture, where control is centralized and removed from individual users,
the concern for integrity has diminished. The massive social media platforms
have created environments where no one feels responsible for the truthfulness or
quality of what circulates.

Web 3.0 is poised to change this dynamic by returning ownership to the data
owners. This is not speculative; it's already emerging. For example,
ActivityPub, the protocol behind de

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