Synthetic human-like fakes: Difference between revisions

'''Definitions'''

<section begin=definitions-of-synthetic-human-like-fakes />

When it cannot be determined by human testing or media forensics whether some fake voice is a synthetic fake of some person's voice, or is it an actual recording made of that person's actual real voice, it is a pre-recorded '''[[Synthetic human-like fakes#Digital sound-alikes|digital sound-alike]]'''.

::[[Synthetic human-like fakes|Read more about '''synthetic human-like fakes''']], see and support '''[[organizations and events against synthetic human-like fakes]]''' and what they are doing, what kinds of '''[[Laws against synthesis and other related crimes]]''' have been formulated, [[Synthetic human-like fakes#Timeline of synthetic human-like fakes|examine the SSFWIKI '''timeline''' of synthetic human-like fakes]] or [[Mediatheque|view the '''Mediatheque''']].

[[File:Screenshot at 27s of a moving digital-look-alike made to appear Obama-like by Monkeypaw Productions and Buzzfeed 2018.png|thumb|right|480px|link=Mediatheque/2018/Obama's appearance thieved - a public service announcement digital look-alike by Monkeypaw Productions and Buzzfeed|{{#lst:Mediatheque|Obama-like-fake-2018}}]]

These industrially produced pornographic delusions are causing great human suffering, especially in their direct victims, but they are also tearing our communities and societies apart, sowing blind rage, perceptions of deepening chaos, feelings of powerlessness and provoke violence. These kinds of '''hate illustration''' increases and strengthens hate feeling, hate thinking, hate speech and hate crimes and tears our fragile social constructions apart and with time perverts humankind's view of humankind into an almost unrecognizable shape, unless we interfere with resolve.

=== Age analysis and rejuvenating and aging syntheses ===

== Digital sound-alikes ==

[[File:Helsingin-Sanomat-2012-David-Martin-Howard-of-University-of-York-on-apporaching-digital-sound-alikes.jpg|right|thumb|338px|A picture of a cut-away titled "''Voice-terrorist could mimic a leader''" from a 2012 [[w:Helsingin Sanomat]] warning that the sound-like-anyone machines are approaching. Thank you to homie [https://pure.york.ac.uk/portal/en/researchers/david-martin-howard(ecfa9e9e-1290-464f-981a-0c70a534609e).html Prof. David Martin Howard] of the [[w:University of York]], UK and the anonymous editor for the heads-up.]]

* [https://www.aiaaic.org/aiaaic-repository/ai-and-algorithmic-incidents-and-controversies/usd-35m-voice-cloning-heist '''''USD 35m voice cloning heist''''' at aiaaic.org], October 2021 AIAAIC repository entry  

<section end=2021 digital sound-alike enabled fraud />

=== Example of a hypothetical 4-victim digital sound-alike attack ===

# Victim #3 - It could also be viewed that victim #3 is our law enforcement systems as they are put to chase after and interrogate the innocent victim #1

# Victim #4 - Our judiciary which prosecutes and possibly convicts the innocent victim #1.

=== Examples of speech synthesis software not quite able to fool a human yet ===

[[File:Spectrogram-19thC.png|thumb|right|640px|A [[w:spectrogram]] of a male voice saying 'nineteenth century']]

== Text syntheses ==

In [[w:natural language processing]] development in [[w:natural-language understanding]] leads to more cunning [[w:natural-language generation]] AI.

[[w:OpenAI]]'s [[w:OpenAI#GPT|w:Generative Pre-trained Transformer]] ('''GPT''') is a left-to-right [[w:transformer (machine learning model)]]-based [[w:Natural-language generation|text generation]] model succeeded by [[w:OpenAI#GPT-2|w:GPT-2]] and [[w:OpenAI#GPT-3|w:GPT-3]]

* [https://www.technologyreview.com/2020/08/14/1006780/ai-gpt-3-fake-blog-reached-top-of-hacker-news/ ''''A college kid’s fake, AI-generated blog fooled tens of thousands. This is how he made it.'''' at technologyreview.com] '''August 2020''' reporting in the [[w:MIT Technology Review]] by Karen Hao about GPT-3.

* [https://analyticssteps.com/blogs/detection-fake-and-false-news-text-analysis-approaches-and-cnn-deep-learning-model '''"Detection of Fake and False News (Text Analysis): Approaches and CNN as Deep Learning Model"''' at analyticsteps.com], a 2019 summmary written by Shubham Panth.

Introduction of [[w:ChatGPT]] by OpenAI brought the need for software to detect machine-generated texts.

== Handwriting syntheses ==

== 2020's synthetic human-like fakes ==

* '''2023''' | '''<font color="green">Law</font>''' | {{#lst:Law on sexual offences in Finland 2023|what-is-it}}  

* <font color="red">'''1999'''</font> | <font color="red">'''institute founded'''</font> | The '''[[w:Institute for Creative Technologies]]''' was founded by the [[w:United States Army]] in the [[w:University of Southern California]]. It collaborates with the [[w:United States Army Futures Command]], [[w:United States Army Combat Capabilities Development Command]], [[w:Combat Capabilities Development Command Soldier Center]] and [[w:United States Army Research Laboratory]].<ref name="ICT-about">https://ict.usc.edu/about/</ref>. In 2016 [[w:Hao Li]] was appointed to direct the institute.  

PROTECTING PRESIDENT ZELENSKYY AGAINST DEEP FAKES https://arxiv.org/pdf/2206.12043.pdf