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Sample Press Release #10 by Kathleen Madrid del Rosario Manuel 12.50 AM 09/08/2022 An easy-to-follow recipe for Skittles vodka. Source: https://www.food.com/recipe/skittles-vodka-379166 ________________________ Making Skittles Vodka Though it has candy in it, this liquor is for adults only so for those of you 18 and above, read on. You can now make candy-flavored vodka using Skittles, one of America’s --- if not the world’s --- most loved candy. Coming up with your Skittles vodka is one way to add flavor and color to regular vodka. Once done, you can drink your Skittles vodka straight, make candy-colored cocktails or use in shot glasses, all to taste the rainbow. To make Skittles vodka, according to www.food.com, you will need 180 ml of vodka and 60 pieces of Skittles in a single color of your choice. After separating Skittles by color, choose one. Get your regular vodka and measure 180 ml. Mix the 60 single-color Skittles to the 180 ml vodka. Place in empty water bottles and shake vigorously until the colors go into the vodka. Leave overnight. Strain the Skittles vodka. Make sure the white residue is removed. Pour your Skittles vodka into a container, jar or bottle. Chill. Once chilled, it’s time to enjoy your Skittles vodka. Enjoy.

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My name is Kathleen and some of the jobs I held were as Communications Specialist and Business Reporter. I am a homeschooling mother now.

I was inspired to research and write this article after reading Tom Taulli’s article, “Facial recognition bans: what do they mean for AI (Artificial Intelligence) in Forbes.com. Here is his article:

https://www.forbes.com/sites/tomtaulli/2020/06/13/facial-recognition-bans-what-do-they-mean-for-ai-artificial-intelligence/?sh=1ea18c6a46ee

 

The New Buzzword is Artificial Intelligence

By Kathleen Madrid del Rosario Manuel

Metro Manila, March 5 2021

Machines should only do what humans cannot. --- Jack Ma

In an article, Alibaba founder Jack Ma: ‘AI will cause more people pain than happiness’

Machines, because of machine learning, and human data scientists who have found a way to aggregate and sift through myriad of data, have brought about a point of view that says machines will automatically replace some humans in jobs.

The human spirit and endurance has been such that spacecraft have astronauts and oil rigs are manned by engineers. The loneliest job in the world, according to an article by Kristina Rudic in vault.com, entitled World’s Loneliest Job, is a fire lookout at Gila National Forest. Gila National Forest, located in New Mexico and a lookout is supposed to warn about fire that may start and consume the forest. Months on end, the looker will be by himself, a pair of binoculars for his companion in his work.

We marvel at the tests of limits and endurance people could take. Loneliness is seen from the outside, with people noticing who they think is lonely when what they really see is a human used to little or no human contact and quite accustomed to it.

That is what the pandemic COVID-19 served to reinterate. That human life is fragile and should matter, whether lonely, alone or not. Here we see how artificial intelligence could make even more people lonely and detached.

What about artificial intelligence and how it is laying claim to the future? AI, hand in hand with machine learning, are producing computers, equipment and robots whom they say will take over our jobs and do our work for us.

The cost of AI has caused a shift in resource management and maximization for companies, both those big companies and medium to small corporations, who now must get data scientists and software and hardware specialists who will feed them dashboard metrics which will supposedly increase productivity, sales, level operations and make their employees, clients, customers and management prepared for the new future (with AI versus a pre-AI future).

I have read articles about the doomsday scenario robots and artificial intelligence will cause to the world population. I get a bit apprehensive everytime, being a mother of children below 18, and aspiring to go back to the workforce and thinking if a self-driving car will make it in the streets of Metro Manila.

I think AI use should be used in three main things. One, is is to increase food security hand-in-hand with the farmers and fishermen and traders, to the supermarkets, stores and restaurants. Two, AI can be used to assist humans, not replace them, their life, their raison d’etre and their work, job, livelihood or business. Three, artificial intelligence has use in cybersecurity.

Artificial intelligence should be there to make us feel secure, not whittle or whitewash us out.

There must be a way for AI to come up with ideas the promote food and job security and decrease the risk of cyberspace attacks on our website real estate.

This idea is to promote robots working for, and alongside humans, instead of being a threat to both job and peace of mind.

Robots are there to assist and not challenge or else there will be selectivity in all aspects. Considering the limitations of neural networks and considering the breakdown of machines and thus constant upkeep, what will happen is we will keep using AI and machine learning in industries and occupations which we no longer want to handle or thrive, or give to the Third-world economies to do as outsourced work.  

It is an idea that AI and machine learning will create a hegemony of work culture, that we get to select which jobs should be peak and increasing in number. Corollarily, that AI and machine learning gets to choose which jobs to render extinct or useless., through robots or machines or programs.

This should not be the case. The selectivity must be such that artificial intelligence should be used to select which industries and professions to favor and make more productive, not curry to or banish.

If we are not careful, what will be left are designers and developers of software, hardware and programs for the robots that increase farm productivity instead of the very humans and institutions they are trying to replace. We will be left with Salesforce engineers and experts and no longer be with the sales personnel who are responsible for doing business and territorial development and expansion or product designers who see how humans actually use and re-use their products and services.

If we do not have AI and machine learning regulations, what we will have a surplus of are data scientists whose predicative ability lies only within the data that was gathered and encoded by humans themselves, the very thing they are trying to replace with the machines they are designing and machine and robot creators and maintenance personnel.

The threat is to remove frontliners and for self-driving cars, the drivers themselves. You go visit a website and what will talk with you are chatbots who seem artificial even though they are intelligent (“Thank you for choosing tulle in white. The feel of tulle is soft and fairy-like.”) Cars may be invented that deliver what you ordered although cannot control when the human steps on something slippery and bashes his head on the car-deliveryman. Human interaction is what is being humanly interrupted.

Although they say that in as little as thirty years, many of the scenarios, actual and imaginable, will have been thought of by data scientists and mined for data, programmed by their AI software engineers and maintained by their AI hardware engineers, one misses the point exactly by going full force with artificial intelligence and machine learning.

Big data, big tech and data science misses the big picture for two reasons. One cannot see and encapsulate all the possible scenarios, including the effects of the emotions and thought processes that come into why humans do something. A machine, though without feeling, is ultimately not afraid or sad but is quite used to being what it is, an object we take pains turning into a pedigreed object that must be maintained.

Data science, data encryption, data encoding and data gathering will be the most sought after jobs as we set to encode and enter data that will be examined, studied and analyzed, for past information, a predictable present and a hoped for future with management-set objectives. This spells a foreboding because jobs will be skewed towards serving the pedigreed objects that are programs and robots, they that are dashboard and metrics sources, and computing jobs.

Another reason big data, data science and big tech do not see is that human explanation separates hard science into soft science. AI cannot begin to figure out why and how humans will do something (like they have come up with AI, machine learning, robots and neural network programming), just that they do.

There will be no rise of the machines but always, a selectivity, on what machines will rise, what industries artificial intelligence could be useful for, and who will be on the receiving end, job-wise and life-wise.

None the wiser, the new buzzword is artificial intelligence but just how intelligent these machines, robots and software and programs are still depends on a human. We must be careful about the rise of these machines because we still need humans for these machines’ upkeep. Enough with the statement the simplistic machines will replace humans and more of using AI and machine learning for the majority and common good.

References:

https://www.theguardian.com/technology/2017/apr/24/alibaba-jack-ma-artificial-intelligence-more-pain-than-happiness

https://www.vault.com/blogs/job-search/the-worlds-loneliest-job

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