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Oxford Mathematician: Atheism Detracts from Science

The problem, as John Lennox sees it, is that atheism does not provide grounds for believing in rationality

Today, Evolution News and Science Today published an excerpt from Oxford mathematician John Lennox’s 2084: Artificial Intelligence and the Future of Humanity (Zondervan 2020): in which Lennox discusses some of the ways in which atheism detracts from science: Science proceeds on the basis of the assumption that the universe is, at least to a certain extent, accessible to the human mind. No science can be done without the scientist believing this, so it is important to ask for grounds for this belief. Atheism gives us none, since it posits a mindless, unguided origin of the universe’s life and consciousness. John Lennox, “Why Science and Atheism Don’t Mix” at Evolution News and Science Today: He offers physicist John Polkinghorne’s explanation of…

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Will Ideas or Algorithms Rule Science Tomorrow?

David Krakauer of the Santa Fe Institute offers an unsettling vision of future science as produced by machines that no one really understands

The basic problem is that accepting on faith what we can’t ever hope to understand is not a traditional stance of science. Thus it’s a good question whether science could survive such a transition and still be recognizable to scientists. But does turning things over to incomprehensible algorithms, as Krakauer proposes, really work anyway? Current results from a variety of areas give pause for thought.

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God’s Existence Is Proven by Science

Arguments for God’s existence can be demonstrated by the ordinary method of scientific inference

If we approach the arguments logically, as the ancient philosophers did, we will see that it is more certain that God exists than that anything else does. Atheist evolutionary biologist Jerry Coyne should consider the arguments more carefully before assuming that prayer is foolish.

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Will an AI Win a Nobel Prize for Science All by Itself One Day?

No, but Support Vector Machines (SVMs) can allow scientists to frame questions so that a comprehensible answer is more likely

AI can certainly help scientists. But to understand why AI can’t do science on its own, we should take a look at the NP-Hard Problem in computer science. The “Hard” is in the name of the problem for a reason… 

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2019 AI Hype Countdown #6: AI Will Replace Scientists!

In May of this year, The Scientist ran a series of pieces suggesting that we could automate the process of acquiring scientific knowledge

In reality, without appropriate human supervision, AI is just as likely to find false or unimportant patterns as real ones. Additionally, the overuse of AI in science is actually leading to a reproducibility crisis.

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Futurism Doesn’t Learn from Past Experience

Technological success stories cannot be extrapolated into an indefinite future

The limits of science can be as instructive as the discoveries. If science someday proved that computer systems could never reproduce some aspect of mind, we'd have learned something important about the nature of mind.

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Science Confronts Credibility Issues?

Not to worry, prestigious researchers blame them on social media trolls and bots
And another thing: The researchers phoned the Seventies and asked them to please come back. Soon. Seriously, that’s the impression I get from reading a paper in PNAS, stemming from the National Academy of Sciences’ Arthur M. Sackler Colloquium November 2017 Read More ›

Does digitization threaten science?

It enables new abuses, according to a Cambridge nanoscientist
The problem is not digitization as such, of course, but the mindset that it inadvertently encourages. Sometimes, for example, “citation rings” agree to cite each other’s papers so as to artificially inflate their rankings. Sometimes it graduates to “citation stacking” Read More ›