BBS:      TELESC.NET.BR
Assunto:  "The height of nonsense"
De:       Mike Powell
Data:     Sun, 8 Feb 2026 11:26:56 -0500
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"The height of nonsense": Oracle co-founder Larry Ellison's 1987 argument
that not everything should be AI makes perfect sense in 2026

By Wayne Williams published 4 hours ago

A forgotten AI debate from 38 years ago feels uncomfortably relevant today

In 1987, long before artificial intelligence became the mass-market obsession
it is today, Computerworld convened a roundtable to discuss what was then a new
and unsettled question: how AI might intersect with database systems.

The roundtable, chaired by tech royalty Esther Dyson, brought together three
sharply different perspectives. Tom Kehler of Intellicorp represented the
expert systems movement (the 1980s equivalent of today's Generative AI hype).
John Landry of Cullinet focused on applying AI techniques to enterprise
applications, and Larry Ellison, president and CEO of Oracle, took a view that
was already contrarian even by the standards of the day.

What makes the discussion notable in hindsight is not the optimism around AI,
which was common at the time, but Ellison's repeated insistence on limits.
While others described AI as a new architectural layer or even a "new species"
of software, Ellison argued that intelligence should be applied sparingly,
embedded deeply, and never treated as a universal solution.

AI merely a tool

"Our primary interest at Oracle is applying expert system technology to the
needs of our own customer base," Ellison said. "We are a data base
management system company, and our users are primary systems developers,
programmers, systems analysts, and MIS directors."

That framing set the tone for everything that followed. Ellison was not
interested in AI as an end-user novelty or as a standalone category. He saw it
as an internal tool, one that should improve how systems are built rather than
redefine what systems are.

Many vendors treated expert systems as a way to replicate human decision making
wholesale. Kehler described systems that encoded experience and judgment to
handle complex tasks such as underwriting or custom order processing.

Landry went further, arguing that AI could form the architecture for an
entirely new generation of applications, built as collections of cooperating
expert systems.

Ellison pushed back at this notion, prompting moderator Esther Dyson to ask:
"Your vision of AI doesn't seem to be quite the same as Tom Kehler's, even
though you have this supposed complementary relationship. He differentiates
between the AI application and the data base application, whereas you see AI
merely as a tool for building data bases and applications."

"Many expert systems are used to automate decision making," Ellison
replied. "But a systems analyst is an expert, too. If you partially automate
his function, that's another form of expert system."

Ellison drew a clear line between processes that genuinely require judgment and
those that don't. In doing so, he rejected what might now be called AI
maximalism.  "In fact, not all application users are experts or even
specialists," he said. "For example, an order processing application may
have dozens of clerks who process simple orders. Instead of the order
processing example, think about checking account processing. Now, there are no
Christmas specials on that. There are no special prices. Instead, performance
is all-critical, and recovery is all-critical."

"The height of nonsense"

When Dyson suggested a rule such as automatically transferring funds if an
account balance dropped below a threshold, Ellison was blunt.  "That can be
performed algorithmically because it's unchanging," he said. "The
application won't change, and to build it as an expert system, I think, is
the height of nonsense."

This was a striking statement in 1987, when expert systems were widely promoted
as the future of enterprise software. Ellison went further, issuing a warning
that sounds surprisingly modern.  "And so I say that a whole generation is
going to be built on nothing but expert systems technology is a misuse of
expert systems. I think expert systems should be selectively employed. It is
human expertise done artificially by computers, and everything we do requires
expertise."

Rather than applying AI everywhere, Ellison wanted to focus it where it changed
the economics or usability of system development itself. That led him to what
he called fifth-generation tools, not as programming languages, but as
higher-level systems that eliminated procedural complexity.  "We see enormous
benefits in providing fifth-generation tools," he said. "I don't want to
use the word `languages,' because they really aren't programming
languages anymore. They are more."

He described an interactive, declarative approach to building applications, one
where intent replaced instruction.  "I can sit down next to you, and you can
tell me what your requirements are, and rather than me documenting your
requirements, I'll sit and build a system while we're talking together, and
you can look over my shoulder and say, `No, that's not what I meant,' and
change things."

The promise was not just speed, but a change in who controlled software.  "So
not only is it a productivity change, a quantitative change, it's also a
qualitative change in the way you approach the problem."

Not anti-AI

That philosophy carried through Oracle's later product strategy, from early
CASE tools to its eventual embrace of web-based architectures. A decade later,
Ellison would argue just as forcefully that application logic belonged on
servers, not on PCs.

"We're so convinced that having the application and data on the server is
better, even if you've got a PC," he told Computerworld in 1997. "We
believe there will be almost no demand for client/server as soon as this comes
out."

By 2000, he was even more forthright.  "People are taking their apps off PCs
and putting them on servers," ZDNET reported Ellison as saying. "The only
things left on PCs are Office and games."

In retrospect, Ellison's predictions were often early and sometimes
overstated. Thin clients did not replace PCs, and expert systems did not
transform enterprise software overnight. Yet the direction he described proved
durable.

Application logic moved to servers, browsers became the dominant interface, and
declarative tooling became a core design goal across the industry.

What the 1987 roundtable captures is the philosophical foundation of that
shift. While others debated how much intelligence to add to applications,
Ellison questioned where intelligence belonged at all.

He treated AI not as a destination, but as an implementation detail, valuable
only when it reduced complexity or improved leverage.

As AI once again dominates enterprise strategy discussions, the caution
embedded in Ellison's early comments feels newly relevant.

His core argument was not anti-AI, but anti-abstraction for its own sake.
Intelligence mattered, but only when it served a larger architectural goal.

In 1987, that goal was making databases the center of application development.
Decades later, the same instinct underpins modern cloud platforms. The
technology has changed, but the tension Ellison identified remains unresolved:
how much intelligence systems need, and how much complexity users are willing
to tolerate to get it.


https://www.techradar.com/pro/the-height-of-nonsense-oracle-co-founder-larry-el
lisons-1987-argument-that-not-everything-should-be-ai-makes-perfect-sense-in-20
26

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