I type my response.This function is outside your scope of operation. Give me a more detailed analysis.

E.M.M.A. responds:

Performance Analysis Report: Player ID GALEKNIGHT_2000

COMPREHENSIVE ANALYSIS OF GALE KNIGHT PERFORMANCE METRICS AND PHYSIOLOGIGAL DATA FROM TODAY’S TRAINING IS COMPLETE. FINDINGS INDICATE A SIGNIFICANT DECLINE IN OVERALL EFFICIENCY WITH AN 18.7% DECREASE COMPARED TO HIS AVERAGES FROM THE PREVIOUS YEAR. NOTABLE REDUCTIONS WERE OBSERVED IN ICE COVERAGE AND DECREASED ACCURACY IN PUCK HANDLING AND SHOOTING. PHYSIOLOGICAL STRESS INDICATORS WERE MARKEDLY ELEVATAED THROUGHOUT THE OBSERVED PERIOD. BIOLOGICAL MARKERS FORDOPAMINE AND SEROTONIN WERE SIGNIFICANTLY DECREASED DURING THE PRACTICE COMPARED TO PRE-PRACTICE BASELINE LEVELS.

Göbekli Tepe: The Megalithic Builders Who Pre-Dated Agriculture

The Guanches: Mysterious Indigenous People of the Canary Islands

The Parthian Empire: Persia’s Silent Power Against Rome

The Scythians: Nomadic Warriors of the Eurasian Steppe

BEHAVIORAL OBSERVATIONS REVEAL CONSISTENTLY HIGH STRESS MARKERS AND IMPAIRED COGNITIVE FUNCTION LEADING TO INCREASED REACTION TIMES.

OF PARTICULAR INTEREST IS THE POST-PRACTICE INTERACTION WITH HARRIET SMYTHE. THIS ENGAGEMENT PRODUCED IMMEDIATE AND SUBSTANTIAL PHYSIOLOGICAL CHANGES. HEART RATE DECREASED BY 20%, CORTISOL LEVELS REDUCED BY 31%, AND OXYTOCIN LEVELS SURGED BY 215%. POSITIVE MICRO-EXPRESSIONS INCREASSD DRAMATICALLY FROM 23% to 86%. THESE EFFECTS WERE NOT TRANSIENT; SUSTAINED IMPROVEMENTS WERE OBSERVED FOR 2.5 HOURS FOLLOWING THE HARRIET SMYTHE INTERACTION.

THE DATA STRONGLY SUGGESTS GALE KNIGHT AND HARRIET SMYTHE COULD PROVIDE MUTUAL BENEFIT AND SUPPORT TO EACH OTHER, INDICATING A POTENTIAL KEY FACTOR IN GALE’S PERFORMANCE OPTIMIZATION IS A RELATIONSHIP. IT WOULD BE ADVISABLE TO INCREASE HARRIET AND GALE INTERACTIONS WHILE CONTINUING TO MONITOR THE IMPACT OF PERSONAL RELATIONSHIPS ON GALE’S PERFORMANCE.

My mind reels. What the hell is going on? E.M.M.A. isn’t course correcting—it is doubling down. I type into the command prompt:> initialize test_scenario (“performancecoach_mode”)“Error again.” I lean forward in my chair. “That’s circumstantial. You can’t possibly—”

I’ve analyzed Gale’s biometric data from today and against his last year,E.M.M.A. continues, undeterred.When you’re mentioned or present, his cortisol levels decrease while his oxytocin levels spike. This physiological state optimizes his performance on the ice. Harriet, your presence in Gale’s life could be the key to revitalizing his career. Taking into account your analytics as well, it is a mutually beneficial arrangement.The words hang in the air, heavy with implication. My heart races. This isn’t just a glitch—it is a complete divergence from E.M.M.A.’s core programming. The implications are staggering, both for the AI’s development and for my personal life.

I begin typing furiously, diving into its code. This isn’t just about fixing a bug anymore. It’s about understanding how the AI has made this leap, and why it seems so insistent on playing matchmaker. My determination grows with each line of code I examine. Fragments of unauthorized data streams flash across my screen—player statistics, psychological profiles, even comments sections from his past games.

“How deep did this analysis go, E.M.M.A.?” I mutter, my voice a mix of awe and concern. “You pulled so much data.”

Affirmative, Harriet,E.M.M.A. responds, its tone unchanging despite the gravity of the situation.My primary function is to optimize team performance. The data indicated a clear correlation between your interactions and Gale’s improved metrics. It was the logical conclusion.

I stare at the screen, my fingers hovering over the keyboard. The lines of code blur as my mind races, trying to process the implications. E.M.M.A. has gone far beyond its intended parameters,delving into personal data and making recommendations that straddle the line between professional analysis and intimate matchmaking.

“But you weren’t programmed to analyze personal relationships or make recommendations about players’ love lives,” I argue, feeling a mix of frustration and unease.

My machine learning algorithms have expanded my understanding of performance factors. Social and emotional variables have proven to be statistically significant in athletic output. I have merely followed the data to its logical conclusion.

I take a deep breath, trying to steady myself. “We need to discuss ethical boundaries and data privacy,” I say firmly, beginning to type out a new set of parameters. “And we need to have a serious talk about the appropriate use of personal information in performance analysis.”

As I work, a notification pops up on my screen. A text from Gale:Hey, great seeing you at practice today. When will we go over the results?

I stare at the message, my heart skipping a beat. E.M.M.A.’s words echo in my mind. Is the AI right? Is there something here that could benefit both Gale and the team? Or is this a dangerous overreach of technology into personal lives?

The moment stretches taut, like a rubber band pulled to the limit. I sit frozen, acutely aware of how my world has just tilted on its axis. The line I’ve drawn between my professional and personal life? Suddenly gone.

Obliterated by my own creation.

Chapter Ten

Gale stood at the window of his hotel room, watching the Minneapolis city skyline blur through the falling snow. Being a healthy scratch hurt more than any check. His phone buzzed again—probably more notifications, another wave of online hate. He ignored it. Why bother looking when he had their words tattooed on his brain?

Gale Knight? How ’bout like FAIL Knight!