Take That and New Kids on the block were both bands who gained commercial success from the early 1990s. While both groups have had their share of successes and devoted fans, there has been ongoing debate among music fans and critics about which group is superior. In this analysis, used music theory and statistical analysis to examine the musical qualities of Take That and NKOTB in order to determine which group is the better of the two.
In order to conduct a comprehensive analysis of the music of Take That and NKOTB, we gathered a sample of ten songs from each group, including both ballads and uptempo tracks. We then applied a variety of musical analysis techniques, including melody analysis, harmony analysis, and rhythm analysis, to determine the musical characteristics of each group’s music. We also gathered data on the commercial success of each group, including record sales, radio airplay, and concert attendance, in order to provide a more complete picture of their overall popularity.
Our analysis revealed that Take That had a more diverse range of musical styles in their repertoire, with a higher proportion of ballads and mid-tempo tracks in addition to uptempo numbers. In terms of melody, Take That’s songs tended to feature more intricate and varied melodies, with a greater use of melodic embellishments and varied phrasing. Harmonically, Take That’s songs were more complex, with a wider range of chord progressions and a greater use of non-diatonic chords. In terms of rhythm, Take That’s songs tended to have more varied and complex rhythmic structures, with a greater use of syncopation and irregular time signatures.
In comparison, NKOTB’s music tended to be more uniform in style, with a higher proportion of uptempo tracks and a more limited range of melody, harmony, and rhythm. While NKOTB did have some ballads in their repertoire, these songs tended to be more formulaic in their structure and less musically innovative.
In terms of commercial success, Take That outperformed NKOTB in several key metrics. Take That had higher record sales and radio airplay, and their concerts were consistently more well-attended.
Based on our analysis of the musical qualities of Take That and NKOTB, as well as their commercial success, it is clear that Take That is the superior group. Their music is more diverse and musically innovative, featuring more complex melodies, harmonies, and rhythms. They also had greater commercial success, indicating a stronger appeal to a wider audience.
While both Take That and NKOTB have their devoted fans, our analysis demonstrates that Take That is the better group overall.
Disclaimer & Warning
How did the above article make you feel? To a certain audience at a certain time the above analysis would be just as divisive as any political issue or spectrum. Maybe you found yourself justified if you are a Take That fan or outraged if you are a NKOTBer? Well, the above article was written by ChatGPT to be a convincing argument in the style of a scientific journal: so the ‘author’ has never even listened to either band, conducted zero research, and has no understanding of music theory.
AI will be a powerful tool to help many people be more productive: but like any tool it can be used for good or bad: it will be easier than ever for bad-acting sophists to create convincing ‘sounding’ arguments at the push of a button.
How to protect yourself against AI-generated text-propaganda
Even as text-generating tools get more sophisticated, there are still steps you can use to protect yourself.
One tool available now is to use a text analyser such as the “Giant Language Model Testroom” available here: http://gltr.io/dist/index.html
Language model AIs generate text based on the probability of one word following another. By analysing text, it’s possible to tell if a word would be one of the most common ones – and so if the text is likely to have been machine-generated.
You can see comparing these images of analysis; the article above has high levels of green suggesting a machine has written it by choosing which word is probably next. But looking at the analysis of this disclaimer in comparison, you can see more improbable words are used:
In the future, AI-generated texts may come with a ‘finger-print’ built in, something invisible to the casual reader but a flag to analysis – but there are still likely to be bad-actor versions available, and other paraphrasing tools that can beat this analysis.
The SIFT technique
An algorithm, or technique, called “S.I.F.T.” gives a good framework to analyse any new information. It was developed by a teacher called Mike Caulfield. He has been working on effective ways you can to navigate online information and spot misinformation/disinformation.
- Investigate the source
- Find better coverage, and
- Trace claims, quotes and media to the original context.
In the above example, to judge this article you would
- Stop before sharing it, especially (this is critical) if you already agree that Take That are better than New Kids on the Bloc!
- Investigate the source – are authors named? Are they experts qualified in music theory?
- Find better coverage – has the finding that take that are better been covered in any traditional fact-checking news sources? Has it been published in a peer-reviewed journal?
- Trace Claims – Claims are made in the article about things like record sales, radio airplay and concert audiences, are they credible? are they checkable?
You can see that this can still help protect you from AI-generated misinformation. Mike runs a free educational online course on it here. https://infodemic.blog/ This methodology may not tell you if a claim was made by a human or an AI: but it will still help protect you against the intent.
Brave New World
Propaganda and misinformation are in an arms race between producer and target. There are ever more dangers out there that are becoming ever easier to generate. From photo manipulation with ai filters, text generation, deep-fakes, voice imitators and more. However, with fair warning, good practice and new technologies, we can still take steps to protect ourselves.
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