Why Artificial Intelligence Isn’t Intelligent
Kanebridge News
    HOUSE MEDIAN ASKING PRICES AND WEEKLY CHANGE     Sydney $1,666,984 (-0.52%)       Melbourne $1,025,140 (-0.29%)       Brisbane $1,079,790 (+0.21%)       Adelaide $987,421 (+0.48%)       Perth $959,727 (+1.13%)       Hobart $774,699 (-0.85%)       Darwin $821,142 (+4.72%)       Canberra $946,671 (-0.99%)       National $1,096,933 (+0.01%)                UNIT MEDIAN ASKING PRICES AND WEEKLY CHANGE     Sydney $779,804 (-0.05%)       Melbourne $501,457 (-0.97%)       Brisbane $680,117 (+0.71%)       Adelaide $516,640 (-0.17%)       Perth $539,067 (+1.01%)       Hobart $528,172 (+0.12%)       Darwin $391,098 (+0.26%)       Canberra $495,303 (+3.15%)       National $576,956 (+0.40%)                HOUSES FOR SALE AND WEEKLY CHANGE     Sydney 12,076 (-85)       Melbourne 14,218 (-287)       Brisbane 8,085 (-106)       Adelaide 2,943 (+40)       Perth 7,410 (-63)       Hobart 1,202 (-4)       Darwin 165 (-4)       Canberra 1,087 (-18)       National 47,186 (-527)                UNITS FOR SALE AND WEEKLY CHANGE     Sydney 9,230 (-171)       Melbourne 7,611 (-611)       Brisbane 1,520 (-30)       Adelaide 404 (-17)       Hobart 212 (+1)       Hobart 215 (-13)       Darwin 287 (+2)       Canberra 1,186 (-1,198)       National 22,003 (-2,039)                HOUSE MEDIAN ASKING RENTS AND WEEKLY CHANGE     Sydney $800 ($0)       Melbourne $595 ($0)       Brisbane $650 ($0)       Adelaide $640 (+$10)       Perth $700 ($0)       Hobart $583 (+$3)       Darwin $720 (-$30)       Canberra $710 ($0)       National $681 (-$3)                UNIT MEDIAN ASKING RENTS AND WEEKLY CHANGE     Sydney $750 ($0)       Melbourne $590 ($0)       Brisbane $650 (+$10)       Adelaide $550 (+$15)       Perth $665 (+$15)       Hobart $500 (+$18)       Darwin $550 (+$35)       Canberra $590 (+$5)       National $615 (+$10)                HOUSES FOR RENT AND WEEKLY CHANGE     Sydney 5,732 (-16)       Melbourne 7,664 (+4)       Brisbane 3,892 (-6)       Adelaide 1,458 (-8)       Perth 2,305 (-13)       Hobart 236 (+7)       Darwin 76 (-1)       Canberra 465 (+5)       National 21,828 (-28)                UNITS FOR RENT AND WEEKLY CHANGE     Sydney 7,852 (-14)       Melbourne 5,484 (0)       Brisbane 1,900 (+20)       Adelaide 413 (-1)       Perth 778 (+6)       Hobart 90 (-8)       Darwin 86 (+7)       Canberra 544 (-22)       National 17,147 (-12)                HOUSE ANNUAL GROSS YIELDS AND TREND       Sydney 2.50% (↑)      Melbourne 3.02% (↑)        Brisbane 3.13% (↓)     Adelaide 3.37% (↑)        Perth 3.79% (↓)     Hobart 3.91% (↑)        Darwin 4.56% (↓)     Canberra 3.90% (↑)        National 3.23% (↓)            UNIT ANNUAL GROSS YIELDS AND TREND       Sydney 5.00% (↑)      Melbourne 6.12% (↑)      Brisbane 4.97% (↑)      Adelaide 5.54% (↑)      Perth 6.41% (↑)      Hobart 4.92% (↑)      Darwin 7.31% (↑)        Canberra 6.19% (↓)     National 5.54% (↑)             HOUSE RENTAL VACANCY RATES AND TREND       Sydney 2.0% (↑)      Melbourne 1.9% (↑)      Brisbane 1.4% (↑)      Adelaide 1.3% (↑)      Perth 1.2% (↑)      Hobart 1.0% (↑)      Darwin 1.6% (↑)      Canberra 2.7% (↑)      National 1.7% (↑)             UNIT RENTAL VACANCY RATES AND TREND       Sydney 2.4% (↑)      Melbourne 3.8% (↑)      Brisbane 2.0% (↑)      Adelaide 1.1% (↑)      Perth 0.9% (↑)      Hobart 1.4% (↑)      Darwin 2.8% (↑)      Canberra 2.9% (↑)      National 2.2% (↑)             AVERAGE DAYS TO SELL HOUSES AND TREND       Sydney 33.9 (↑)        Melbourne 32.6 (↓)     Brisbane 35.9 (↑)      Adelaide 30.2 (↑)      Perth 41.5 (↑)      Hobart 37.1 (↑)        Darwin 23.7 (↓)     Canberra 35.3 (↑)      National 33.8 (↑)             AVERAGE DAYS TO SELL UNITS AND TREND       Sydney 32.6 (↑)      Melbourne 32.8 (↑)        Brisbane 31.9 (↓)     Adelaide 29.3 (↑)      Perth 41.0 (↑)      Hobart 37.4 (↑)        Darwin 41.2 (↓)     Canberra 42.9 (↑)      National 36.1 (↑)            
Share Button

Why Artificial Intelligence Isn’t Intelligent

Some experts in AI think its name fuels confusion and hype of the sort that led to past ‘AI winters’ of disappointment.

By Christopher Mims
Tue, Aug 3, 2021 10:34amGrey Clock 5 min

A funny thing happens among engineers and researchers who build artificial intelligence once they attain a deep level of expertise in their field. Some of them—especially those who understand what actual, biological intelligences are capable of—conclude that there’s nothing “intelligent” about AI at all.

“In a certain sense I think that artificial intelligence is a bad name for what it is we’re doing here,” says Kevin Scott, chief technology officer of Microsoft. “As soon as you utter the words ‘artificial intelligence’ to an intelligent human being, they start making associations about their own intelligence, about what’s easy and hard for them, and they superimpose those expectations onto these software systems.”

This might seem like a purely academic debate. Whatever we call it, surely what matters most about “AI” is the way it is already transforming what can seem like almost every industry on earth? Not to mention the potential it has to displace millions of workers in trades ranging from white to blue-collar, from the back office to trucking?

And yet, across the fields it is disrupting or supposed to disrupt, AI has fallen short of many of the promises made by some of its most vocal advocates—from the disappointment of IBM’s Watson to the forever-moving target date for the arrival of fully self-driving vehicles.

Words have power. And—ask any branding or marketing expert—names, in particular, carry weight. Especially when they describe systems so complicated that, in their particulars at least, they are beyond the comprehension of most people.

Inflated expectations for AI have already led to setbacks for the field. In both the early 1970s and late 1980s, claims similar to the most hyperbolic ones made in the past decade—about how human-level AI will soon arise, for example—were made about systems that would seem primitive by today’s standards. That didn’t stop extremely smart computer scientists from making them, and the disappointing results that followed led to “AI winters” in which funding and support for the field dried up, says Melanie Mitchell, an AI researcher and professor at the Santa Fe Institute with more than a quarter-century of experience in the field.

No one is predicting another AI winter anytime soon. Globally, US$37.9 billion has been invested in AI startups in 2021 so far, on pace to roughly double last year’s amount, according to data from PitchBook. And there have also been a number of exits for investors in companies that use and develop AI, with $14.4 billion in deals for companies that either went public or were acquired.

‘You have test tubes, a computer and your machine learning.’

— Viral Shah, CEO of Julia Computing

But the muddle that the term AI creates fuels a tech-industry drive to claim that every system involving the least bit of machine learning qualifies as AI, and is therefore potentially revolutionary. Calling these piles of complicated math with narrow and limited utility “intelligent” also contributes to wild claims that our “AI” will soon reach human-level intelligence. These claims can spur big rounds of investment and mislead the public and policy makers who must decide how to prepare national economies for new innovations.

Inside and outside the field, people routinely describe AI using terms we typically apply to minds. That’s probably one reason so many are confused about what the technology can actually do, says Dr. Mitchell.

Claims that AI will soon significantly exceed human abilities in multiple domains—not just in very narrow tasks—have been made by, among others, Facebook Chief Executive Mark Zuckerberg in 2015, Tesla CEO Elon Musk in 2020 and OpenAI CEO Sam Altman in 2021.

OpenAI declined to comment or make Mr. Altman available. Tesla did not respond to a request for comment. Facebook’s vice president of AI, Jerome Pesenti, says that his company believes the field of AI is better served by more scientific and realistic goals, rather than fuzzy concepts like creating human-level or even superhuman artificial intelligence. “But,” he adds, “we are making great strides toward learning more like humans do, and creating more general-purpose models that perform well on tasks beyond those they are specifically trained to do.” Eventually, he believes this could lead to AI that possesses “common sense.”

The tendency for CEOs and researchers alike to say that their system “understands” a given input—whether it’s gigabytes of text, images or audio—or that it can “think” about those inputs, or that it has any intention at all, are examples of what Drew McDermott, a computer scientist at Yale, once called “wishful mnemonics.” That he coined this phrase in 1976 makes it no less applicable to the present day.

“I think AI is somewhat of a misnomer,” says Daron Acemoglu, an economist at Massachusetts Institute of Technology whose research on AI’s economic impacts requires a precise definition of the term. What we now call AI doesn’t fulfil the early dreams of the field’s founders—either to create a system that can reason as a person does, or to create tools that can augment our abilities. “Instead, it uses massive amounts of data to turn very, very narrow tasks into prediction problems,” he says.

When AI researchers say that their algorithms are good at “narrow” tasks, what they mean is that, with enough data, it’s possible to “train” their algorithms to, say, identify a cat. But unlike a human toddler, these algorithms tend not to be very adaptable. For example, if they haven’t seen cats in unusual circumstances—say, swimming—they might not be able to identify them in that context. And training an algorithm to identify cats generally doesn’t also increase its ability to identify any other kind of animal or object. Identifying dogs means more or less starting from scratch.

The vast sums of money pouring into companies that use well-established techniques for acquiring and processing large amounts of data shouldn’t be confused with the dawn of an age of “intelligent” machines that aren’t capable of doing much more than narrow tasks, over and over again, says Dr. Mitchell. This doesn’t mean that all of the companies investors are piling into are smoke and mirrors, she adds, just that many of the tasks we assign to machines don’t require that much intelligence, after all.

Mr. Scott describes AI in similarly mundane terms. Whenever computers accomplish things that are hard for humans—like being the best chess or Go player in the world—it’s easy to get the impression that we’ve “solved” intelligence, he says. But all we’ve demonstrated is that in general, things that are hard for humans are easy for computers, and vice versa.

AI algorithms, he points out, are just math. And one of math’s functions is to simplify the world so our brains can tackle its otherwise dizzying complexity. The software we call AI, he continues, is just another way to arrive at complicated mathematical functions that help us do that.

Viral Shah is CEO of Julia Computing, a cloud-software company that makes tools for programmers who build AI and related systems. His customers range from universities working on better batteries for electric vehicles to pharmaceutical companies searching for new drugs.

Dr. Shah says he loves to debate how “AI” should be described and what that means for its future abilities, but he doesn’t think it’s worth getting hung up on semantics. “This is the approach we’re taking,” he says. “Let’s not talk about the philosophical questions.”

For consumers, practical applications of AI include everything from recognizing your voice and face to targeting ads and filtering hate speech from social media. For engineers and scientists, the applications are, arguably, even broader—from drug discovery and treating rare diseases to creating new mathematical tools that are broadly useful in much of science and engineering. Anyplace that advanced mathematics is applied to the real world, machine learning is having an impact.

“There are realistic applications coming out of the current brand of AI and those are unlikely to disappear,” says Dr. Shah. “They are just part of the scientist’s toolbox: You have test tubes, a computer and your machine learning.”

Once we liberate ourselves from the mental cage of thinking of AI as akin to ourselves, we can recognize that it’s just another pile of math that can transform one kind of input into another—that is, software.

In its earliest days, in the mid-1950s, there was a friendly debate about what to call the field of AI. And while pioneering computer scientist John McCarthy proposed the winning name—artificial intelligence—another founder of the discipline suggested a more prosaic one.

“Herbert Simon said we should call it ‘complex information processing,’ ” says Dr. Mitchell. “What would the world be like if it was called that instead?”



MOST POPULAR

Hoping to recreate a freewheeling world tour from their youth, two retirees set themselves a ‘no itinerary’ challenge: Can they improvise their way across seven countries?

Super isn’t your only option. These smart strategies can help you self-fund a comfortable retirement.

Related Stories
Money
7 Ways To Self-Fund Your Retirement Beyond Just Your Super
By Helen Baker 21/05/2025
Money
BHUTAN LAUNCHES WORLD-FIRST NATIONAL CRYPTO PAYMENT SYSTEM FOR TOURISM
By Jeni O'Dowd 14/05/2025
Money
9 Ways the Latest Rate Cuts Can Save You $10,000 a Year
By Helen Baker 06/05/2025
7 Ways To Self-Fund Your Retirement Beyond Just Your Super

Super isn’t your only option. These smart strategies can help you self-fund a comfortable retirement.

By Helen Baker
Wed, May 21, 2025 3 min

Superannuation is the first thought when it comes to self-funding retirement. Yet it is hardly the only option for doing so.

Just as we have a choice in how and where we work to earn a living, many people also have a choice in how to fund their retirement.

It is possible and sometimes preferable to leave your superannuation untouched, allowing it to continue growing. Some or all of your income can come from alternative sources instead.

Here are some alternatives you can consider.

1. Downsize your home

For many who own their own homes, the equity accrued over decades can eclipse the funds in superannuation. However, it’s theoretical money only until it is unlocked.

Selling up the family home and downsizing – or rightsizing – for retirement allows you to pocket those gains tax-free and simultaneously relocate to a more suitable home with lower upkeep costs.

Up to $300,000 from the proceeds can be contributed by a downsizer to boost your super, and the remainder can be used to fund living expenses or actively invested.

Remember that while the sale proceeds of your home are tax-free, any future profits or interest earned from that money will be taxable.

2. Part-time work

Semi-retirement allows you to gradually step into retirement. You continue earning income and super while working part-time, keeping a foot in the workforce while testing the waters of your new found free time.

Doing so also offers scope to move into different roles, such as passing on your skills to future generations by teaching/training others in your field of expertise, or taking employment in a new area that interests you and is closer to home.

3. Self-employment

Retirement from a full-time position presents a good opportunity to pursue self-employment. With more time and fewer commitments on your hands, you have greater scope to turn your hobby into a business or leverage your professional skills and reputation as an external consultant.

Also, for the self-employed and those with a family business, director’s loan repayments from the company are typically tax-free, offering a potentially lucrative source of

income and a means of extracting previous investments into the business without selling your ownership stake.

Helen Baker

4. Investments

Rental property income (from residential or commercial properties) can supplement or even provide a generous source of income. The same applies to dividends from shares.

These are likely to be more profitable if you own them well before retirement.

Income that is surplus to your everyday needs can be reinvested using tax-effective strategies to grow your future returns.

5. Family trust

A family trust could be used to house investments for yourself and other relatives, building intergenerational wealth.

Trusts allow funds to be allocated to beneficiaries to manage marginal tax rates and stretch the money further, you have control over how income is split between different family members and have flexibility for changing circumstances.

6. Selling collectables

You may not realise the value of items you have collected over the years, such as wine, artwork, jewellery, vintage cars, and antiques.

Rather than have them collect dust or pay to store them, they could be sold to fund your living costs or new investments.

Where possible, avoid selling growth assets in a depressed market – wait until you can extract maximum value.

7. Obtaining a part-pension

Part-pensions are not only possible but valuable in making your superannuation stretch further. They still entitle you to a concession card with benefits in healthcare, transport, and more.

Take these savings even further by requesting pensioner discounts with other companies, on everything from utilities to travel and insurance to eating out.

Also, don’t overestimate the value of your assets as part of the means test. It’s a common mistake that can wrongly deny you a full or part-pension.

Plan ahead

However, you ultimately fund your retirement, planning is crucial. Advice would hopefully pay for itself.

Understand your spending and how those habits will change before and during retirement, then look to investments that offer the best fit.

Consider a mixture of strategies to diversify your risk, manage your tax liabilities and ensure ongoing income.

Above all, timing is key. The further ahead you plan, the more time you have to embrace additional opportunities and do things at the right time to maximise their value. You’ve worked hard and now is your chance to enjoy the fruits of your labour!

Helen Baker is a licensed Australian financial adviser and author of the new book, Money For Life: How to build financial security from firm foundations (Major Street Publishing $32.99). Find out more at www.onyourowntwofeet.com.au 

MOST POPULAR

An architect’s own home, this Tamarama beach house has been created with love. 

The Mayfair home, listed for £8.25 million, once belonged to the Earls of Lindsay.

Related Stories
Property of the Week
Property of the Week: 26-27 Olola Rd, Vaucluse
By KIRSTEN CRAZE 13/12/2024
Money
Gold Is Beating Everything. How to Get a Piece of the Action
By JACK HOUGH 24/04/2025
Money
The Japanese Sake Masters Swimming Against a Rising Tide of Whisky
By DON NICO FORBES 19/03/2025
0
    Your Cart
    Your cart is emptyReturn to Shop