ML Fairness

I woke up before 7:30. The sleep app showed that I had woken up several times during the night, but it gave me a score of 92%. I started my usual morning routine. I treated myself for sensitivities to tomatoes.
Through e-mail, I read about ML fairness. ML stands for machine learning. This means Google is training their software to identify sites that are right-wing or don't conform to what they think is fair due to their socio-political agenda. Never mind that they have signed deals with pharmaceutical companies. Then the targeted sites get demoted in search results or removed completely. Also, auto-complete uses terms Google staff think that people OUGHT to be searching for, not what other people actually HAVE searched for. I posted an article about it on my Facebook page. Then I found a search engine called GIBIRU that does not alter search results or record search terms.
I made and ate breakfast and listened to interviews. I got dressed and packed for quilting and swimming. I searched around the house for my keys. Over and over again. I tried to retrace my steps from yesterday and found the keys and mail on the chair on the front porch. I had laid them there while I watered the plants yesterday. I put my machine in the car and went to quilting.
The turn out was small, or lots of ladies had left. After some conversation, I set up my machine and started sewing orange blocks. When I ran out, I cut some more rectangles from the orange fabric. I also sewed a seam on another project. Most of the ladies packed up and left. I helped Pat close up and I left, too.
I drove to Jennifer's house. Although it had been sunny and hot all morning, the clouds rolled in and I felt some rain drops when I got there. Her daughter and friends had just left the pool to go shopping. I put my bathing suit on and we got in her pool. She walked back and forth, scooping blossoms and leaves from the pool. I swam around, having a great time. We conversed easily.
Later I got out to use the bathroom. She got out too, so I also dried off and changed back into my clothes. We chatted as she fixed supper and showed me packages of healthy things she had bought. We ate pork meatballs, rice noodles, and zuchini and squash. For dessert, she make chocolate pudding from avocados, cacao powder, banana and coconut milk. We chatted a little longer and then I realized how late it was. I thanked her and ran to my car.
I got home a little after 7. I ran to the bathroom, and then got on Skype. My tapping buddy had already messaged me. I messaged her back and she called. We talked about her week and then about mine. It was over an hour later when we finally got around to tapping. We tapped for two hours but we really dealt with the issue. We both felt better.
After the call, I messaged Chris. He called me and we chatted face to face. We reviewed our Netflix queue and found the selections inexplicable. Jennifer's husband likes to buy coffee beans from foreign countries so I asked Chris if he knew someone in Honduras with a coffee farm. We were both tired, so we ended the call. I took some evening supplements. I got dressed for bed and swished as I wrote my blog post.